INDUSTRIAL TECHNOLOGIES Theory Section – Sergio Terzi

INDUSTRIAL TECHNOLOGIES Theory Section – Sergio Terzi – Year 2019-20

Annotations The parts coloured in grey like this one is the notes written by during the lessons, while the black ones are taken from the slides given by the professor. Inside this document there is the theoretical topic of the course. The information written in this document are not enough to pass the exam, there are also some books suggested by the professor, and obviously the content of the course may change during the years

Michela Beraldo [email protected]

Summary

01. Introduction to production systems ...... 2

1 PRODUCTION FACTORS ...... 2 2 PRODUCTION PROCESS ...... 2 3 PRODUCTION AND LOGISTICS ...... 2 4 PRODUCTION AND OTHERS INDUSTRIAL PROCESSES ...... 3 5 HOW TO DEFINE A PRODUCTION SYSTEM ...... 3 PRODUCTION PROCESS ...... 4 TECHNICAL DRAWINGS...... 5 5.2.1 List of parts & Bill of materials ...... 6 CYCLE TIME ...... 7 5.3.1 Production program / Work order ...... 7 PRODUCTION PLANT ...... 7 5.4.1 Flow sheet of a production plant ...... 8 5.4.2 Layout of a production plant ...... 8

6 TYPES OF PRODUCTION TECHNOLOGIES ...... 9 7 WORTMANN CLASSIFICATION ...... 9 8 CLASSIFICATION OF PRODUCTION SYSTEMS ...... 10 9 EXAMPLE OF PRODUCTION SYSTEMS ...... 12 FERRARI ...... 12 AIRBUS ...... 13 ILLY CAFFÈ ...... 13 THOUGHT QUESTIONS ...... 13 02. Production system KPIs and costs...... 14

1 HOW PRODUCTION SYSTEMS WORK ...... 14 2 PERFORMANCES OF PRODUCTION SYSTEMS...... 15 3 THE CONCEPT OF LEAD TIME ...... 16 4 PRODUCTION TIME ...... 16 4.1.1 Examples ...... 18

5 COSTS OF PRODUCTION SYSTEMS ...... 19 6 HOW TO EVALUATE AN INVESTMENT IN PRODUCTION ...... 20 7 THOUGHT QUESTIONS ...... 20 03. Introduction to the design of production systems (Factory Planning) ...... 21

1 DESIGN PROCESS ...... 21 2 INTEGRATED DESIGN AND ENGINEERING PROCESS ...... 22 JUST AN EXAMPLE ...... 22 3 PRODUCTION SYSTEM DESIGN AND ENGINEERING ...... 24 TYPICAL ACTIVITIES OF SUCH DESIGN SUB-PROCESS ...... 24 3.1.1 Terminology...... 25

4 FACTORY PLANNING MODELS FRAMEWORK ...... 25 5 FROM PROCESS PLANNING TO FACTORY PLANNING ...... 26 04. Design of Manufacturing Systems – Job Shop ...... 27

Summary

6 OUTLINE ...... 27 7 JOB SHOP – GENERAL FEATURES ...... 27 7.1.1 Layout(*) and organisation of resources in the plant ...... 28 7.1.2 Products, processes and product routings ...... 28 7.1.3 Product routings and logistics in the factory ...... 28 7.1.4 Human resources and organisation of resources in the plant ...... 29

8 STRENGHTS ...... 29 FLEXIBILITY ...... 29 8.1.1 Definitions (conceptual) ...... 29 8.1.2 Different dimensions ...... 30 8.1.3 Mix flexibility ...... 30 8.1.4 Volume flexibility ...... 31 8.1.5 Product flexibility ...... 31 8.1.6 Expansion flexibility ...... 31 FURTHER STRENGHTS ...... 32 8.2.1 Low impact of machine breakdowns ...... 32 8.2.1.1 Obsolescence – short introduction of this concept ...... 32 8.2.2 Low obsolescence of the production system ...... 32

9 WEAKNESSES ...... 33 RELATIONSHIP B/W FLEXIBILITY AND PRODUCTIVITY ...... 33 PRODUCTION MANAGEMENT IS DIFFICULT ...... 34 9.2.1 Effects of this difficulty are resulting in subsequent performances ...... 34 9.2.2 Weakness in the system design ...... 35 9.2.3 Example 1 ...... 36 9.2.3.1 Metal processing / working ...... 36 9.2.3.2 Annex ...... 36 9.2.3.3 Turning (external / internal) ...... 36 9.2.3.4 Milling machine ...... 37 9.2.3.5 Sawing machine ...... 37 9.2.3.6 Welding machinery (from http://en.wikipedia.org/wiki/Metalworking) ...... 37 9.2.3.7 Grinding machine / grinder (normally a finishing process) ...... 37 9.2.3.8 Deburring machinery (another finishing process) (Sentences taken from OEM web sites) ...... 37 9.2.4 Example 2 ...... 38 9.2.5 Example 3 ...... 38

10 TYPICAL QUESTIONS RELATED TO SYSTEM DESIGN ...... 38 11 ROUGH DESIGN OF A JOB-SHOP ...... 39 STEP 1 ...... 39 STEP 2 ...... 39 STEP 3 ...... 39 STEP 4 ...... 39 STEP 5 ...... 40 11.5.1 The coefficients are given: these indexes have been codified during the years, during the years the industry collect the data; until that estimations, we have to do some assumption and hypothesisCoefficients (measuring time losses, cfr. Turco) ...... 40 STEP 6 ...... 41 STEP 7 ...... 41 STEP 8 ...... 41 12 EXAMPLE ...... 42 05. Design of Manufacturing Systems – Manufacturing Cells ...... 44

Summary

1 OUTLINE ...... 44 2 GENERAL FEATURES ...... 44 2.1.1 Examples ...... 46 2.1.1.1 Example 1 ...... 46 2.1.1.2 Example 2 ...... 47 2.1.1.3 Example 3 ...... 48 2.1.1.4 Some other examples...... 48 3 STRENGTHS ...... 48 4 WEAKNESSES ...... 51 5 GROUP TECHNOLOGY ...... 52 STEPS ...... 52 6 FIRST METHOD - IDENTIFICATION BASED ON THE CLASSIFICATION OF PRODUCTS ...... 53 INFORMAL METHODS ...... 55 6.1.1 Based on geometrical features of products ...... 55 6.1.2 Based on technological features of products, ...... 55 PART CODING ANALYSIS (PCA) ...... 55 6.2.1 Part coding analysis (example 1) ...... 56 6.2.2 Part coding analysis (example 2) ...... 56 6.2.3 Examples of part coding methods ...... 57 6.2.3.1 Code hierarchical structure ...... 57 6.2.3.2 Polycode structure ...... 57 6.2.3.3 Hybrid structure ...... 57 6.2.3.4 The Optiz Classification System ...... 57 6.2.3.5 Example ...... 58 7 SECOND METHOD - IDENTIFICATION BASED ON PRODUCTION FLOW ANALYSIS (PFA) ...... 58 PRODUCTION FLOW ANALYSIS (PFA) ...... 59 7.1.1 Rank Order Clustering...... 60 7.1.1.1 Example ...... 60 SIMILARITY COEFFICIENTS ...... 62 7.2.1 Example ...... 63

8 ROUGH DESIGN OF A MANUFACTURING CELL ...... 64 IMPROVING LAYOUTS USING CELLS ...... 65 9 VIRTUAL CELLULAR MANUFACTURING ...... 65 10 QUESTIONS FOR REVISION ...... 66 11 REFERENCES ...... 66 06. Design of Production Systems – Transfer Lines ...... 67

III

Summary

1 CLASSIFICATION OF PRODUCTION SYSTEMS...... 67 2 OUTLINE ...... 67 3 GENERAL FEATURES ...... 67 PRODUCTS, PROCESSES AND PRODUCT ROUTINGS ...... 67 3.1.1 Part transfer: ...... 68 3.1.2 Transfer Lines ...... 69 3.1.3 Example 1 ...... 69 3.1.4 Example 2 ...... 70 3.1.5 Example 3 ...... 71 3.1.6 Example ...... 71 3.1.7 Some examples ...... 71

4 STRENGHTS ...... 72 4.1.1 Subsequent performances ...... 73 4.1.2 Other strengths ...... 73

5 WEAKNESSES ...... 73 5.1.1 Other weaknesses: ...... 74

6 INITIAL CONSIDERATIONS FOR DESIGN ...... 75 7 ROUGH DESIGN OF A TRANSFER LINE (SINGLE-MODEL) ...... 75 7.1.1 Define the technological routing and operations of the product type ...... 75 7.1.2 Identify all the machine types that are needed and balance the line on the given CT ...... 75 7.1.3 Calculate the theoretical production capacity ...... 76 7.1.4 Calculate the actual production capacity ...... 76 7.1.5 Compare the actual production capacity and the demand...... 76 MACHINE IDENTIFICATION AND LINE BALANCING ...... 77 7.2.1 Define operations and their sequence ...... 77 7.2.2 Get the required cycle time ...... 77 7.2.2.1 Cycle time ...... 78 7.2.3 Minimum number of workstations ...... 78 7.2.4 Allocate the operations to workstations ...... 78 7.2.5 Line balancing ...... 78 7.2.5.1 Example of line balancing ...... 79 7.2.5.2 Introduction to the example ...... 79 7.2.5.3 Line balancing – Parallel stations ...... 80 7.2.5.4 Another example ...... 80 7.2.5.5 Objectives of line balancing and assigning tasks to workstations ...... 80 7.2.5.6 Compute the efficiency of the solution ...... 81 7.2.6 Assignment of personnel ...... 81 7.2.6.1 Example ...... 81 8 MODELS FOR LINE BALANCING ...... 81 MODELS FOR LINE BALANCING – LINEAR PROGRAMMING ...... 82 8.1.1 Main assumptions of the model: ...... 82 8.1.2 Objective function ...... 82 8.1.2.1 Meaning of the constraints: ...... 83 MODELS FOR LINE BALANCING – FIXED UTILIZATION...... 83 8.2.1 Steps ...... 83 8.2.2 Basic Criteria ...... 83 8.2.3 Example ...... 83 8.2.4 Fixed utilization with local rules ...... 84 8.2.4.1 Processing times ...... 84 FIXED UTILIZATION WITH LOCAL RULES ...... 84 8.3.1 MaxDur ...... 84 8.3.2 MaxNFol ...... 85 8.3.3 Ranked Positional Weighting ...... 85 8.3.4 Prioritization – steps ...... 86 8.3.5 Example ...... 86 8.3.5.1 STEP 1 – Task ordering...... 86 8.3.5.2 STEP 2 – Task assignment...... 86 8.3.6 Assumptions ...... 87

9 ROUGH DESIGN OF A TRANSFER LINE (MULTI-MODEL) ...... 87 10 QUESTIONS FOR REVISION ...... 88 11 REFERENCES ...... 88 07. Design of assembly lines, cells and shops ...... 89

Summary

1 CLASSIFICATION OF PRODUCTION SYSTEMS...... 89 2 ASSEMBLY SYSTEMS – GENERAL FEATURES ...... 89 OTHER GENERAL FEATURES ...... 92 CLASSIFICATION ...... 92 2.2.1 Classification according to the layout configuration ...... 92 2.2.2 Classification according to the production mix management ...... 93 2.2.3 Classification according to reciprocal movements ...... 93 2.2.4 How can we collect time and standard deviation ...... 95 METHODS TO CALCULATE ASSEMBLY TIMES ...... 95 2.3.1 Work sampling ...... 95 2.3.2 Standard times ...... 95 2.3.3 MTM (Motion Time Measurement) method ...... 96 2.3.3.1 Example of a MTM reach table ...... 96 3 FIXED POSITION ASSEMBLY ...... 97 GENERAL FEATURES ...... 97 3.1.1 Description of this type of system ...... 97 3.1.2 Characteristics of products typically assembled by this type of system ...... 97 3.1.3 System characteristics and criticalities: ...... 98 3.1.4 Physical structure and organization of the single site: ...... 98 EXAMPLES ...... 98 3.2.1 Case of small products ...... 98 3.2.1.1 Introduction ...... 98 3.2.1.2 Comments on the fixed position assembly of this case ...... 98 3.2.2 Case of (rather) small and fragile products ...... 99 3.2.3 Case of heavy and bulky products ...... 99 STRENGTHS ...... 99 3.3.1 High flexibility ...... 99 3.3.2 Low investment ...... 99 3.3.3 Job enlargement, enrichment and rotation for the employee ...... 100 WEAKNESSES ...... 100 3.4.1 Potentials for intertwining of material flows ...... 100 3.4.2 High WIP ...... 100 3.4.3 Large space requirement...... 100 3.4.4 Labor training might be difficult and time-consuming ...... 100 3.4.5 High cost for workforce ...... 100 ROUGH DESIGN OF A FIXED POSITION ASSEMBLY ...... 101 4 ASSEMBLY SHOP ...... 101 GENERAL FEATURES ...... 101 HANDLING SYSTEM ...... 102 4.2.1 Examples ...... 102 STRENGTHS & WEAKNESSES ...... 103 4.3.1 Strengths ...... 103 4.3.2 Weaknesses ...... 103

5 ASSEMBLY CELL...... 103 6 ASSEMBLY LINE ...... 104 GENERAL FEATURES ...... 104 6.1.1 System description ...... 104 6.1.2 Types of product ...... 104 6.1.3 System characteristics and criticalities: ...... 104 6.1.4 Physical structure and organization of the line: ...... 105 EXAMPLES ...... 105 STRENGTHS ...... 106 6.3.1 Rationalization of material flows ...... 106 6.3.2 Low WIP ...... 106 6.3.3 Limited space requirement ...... 106 6.3.4 Labour training might be easy...... 106 6.3.5 Low cost for workforce ...... 106 WEAKNESSES ...... 106 6.4.1 Low flexibility ...... 106 6.4.2 Long time required to start new productions ...... 107 6.4.3 Repetitive work ...... 107 6.4.4 Line balancing might be difficult ...... 107 TYPES OF ASSEMBLY LINES ...... 107

Summary

6.5.1 Paced line (constrained; always synchronous)...... 107 6.5.2 Unpaced line (non-constrained) ...... 107 PACED LINES ...... 108 6.6.1 Machine-paced lines ...... 108 6.6.2 Operator-paced lines ...... 108 6.6.3 Continuous flow paced lines ...... 109 6.6.4 Continuous flow lines problem ...... 110 6.6.4.1 Case 1: operators can’t stop the line ...... 110 6.6.4.2 Case 2: operators can stop the line ...... 110 UNPACED LINES ...... 110 6.7.1 Strengths ...... 111 6.7.2 Weaknesses ...... 111 6.7.3 Examples ...... 111

7 DESIGN OF A MANUAL ASSEMBLY LINE ...... 112 SHORT INTRO ON CONSTRAINTS (INPUTS) ...... 112 7.1.1 Input 1 ...... 112 7.1.2 Input 2 ...... 112 7.1.3 Input 3 ...... 112 7.1.4 Design problem ...... 113 7.1.5 Assembly process ...... 113 7.1.6 Number of single sites/stations ...... 113 BALANCING CONSTRAINTS ...... 113 7.2.1 Respect the cycle time ...... 113 7.2.2 Respect the relationships among operations...... 113 7.2.3 Incompatibility between operations that cannot be assigned to the same station (negative zoning)...... 113 7.2.4 Opportunity or necessity to assign some operations to the same station (positive zoning) ...... 114 BALANCING OBJECTIVES ...... 114 7.3.1 Technical objectives ...... 114 7.3.2 Economic objectives ...... 115 LINE BALANCING – PROBABILITY OF NO-COMPLETION ...... 116 7.4.1 Characteristic of this method: ...... 117 7.4.2 Steps of the method: ...... 117 7.4.3 Values of Φ(Zk) ...... 118 7.4.4 Demonstration of the relation Pk = 1 – Φ(Zk) ...... 118 7.4.5 Example ...... 119

8 MANUAL ASSEMBLY SYSTEMS ...... 119 GENERAL FEATURES ...... 119 SINGLE MODEL ...... 119 MULTI-MODEL ...... 119 8.3.1 General features ...... 119 8.3.2 Set-up of multi-model lines: ...... 120 8.3.3 Multi-model line balancing...... 121 MIXED-MODEL ...... 122 8.4.1 General features ...... 122 8.4.2 Production sequencing - Objectives: ...... 123 8.4.3 Line balancing - Objectives ...... 123 8.4.3.1 Example – station balancing: ...... 123 8.4.3.2 Steps ...... 124 9 DESIGN OF UNPACED LINES - BUFFER SIZE ...... 125 9.1.1 Buffers between stations: ...... 125 9.1.2 Decoupling function...... 125 9.1.3 Effect of buffer in a line ...... 125 9.1.3.1 Example 1 ...... 125 10 DESIGN OF CONTINUOUS FLOW LINES – STATION LENGTH ...... 127 10.1.1 Open stations ...... 129 10.1.2 Closed station ...... 129

11 ASSEMBLY LINE – EXAMPLE ...... 130 11.1.1 Bottling line ...... 130

12 AUTOMATED ASSEMBLY ...... 130 13 QUESTIONS FOR REVISION ...... 132 14 REFERENCES ...... 132

Summary

08. Factory Layout Planning ...... 133

1 INTEGRATED DESIGN PROCESS ...... 133 LAYOUT OF A PRODUCTION PLANT ...... 134 FACTORY PLANNING MODEL FRAMEWORK ...... 134 2 FACTORY LAYOUT PLANNING (FLP) ...... 135 OBJECTIVES OF THE FLP PROBLEM ...... 135 MODELS FOR FLP ANALYSIS ...... 136 2.2.1 Formulate the problem as objective functions with given constraints (linear programming models) ...... 136 FLP METHODOLOGY: PHASES OF THE PROJECT ...... 136 PRODUCT ANALYSIS ...... 137 MATERIAL FLOW ANALYSIS ...... 138 PRODUCT AND MATERIAL FLOW ANALYSIS ...... 138 GRAPH AND SPACE DIAGRAM ...... 138 FACTORY LAYOUT DRAWING ...... 139 FLP METHODOLOGY: RELATIONSHIP ANALYSIS ...... 139 3 FLOW ANALYSIS VS RELATIONSHIP ANALYSIS ...... 140 4 METHODS AND CRITERIA FOR FLP PLANNING ...... 140 HEURISTIC TECHNIQUES FOR THE SOLUTION SEARCH ...... 140 4.1.1 Heuristic MAT (Modular Allocation Technique) – starting from green field ...... 141 COMPUTERIZED LAYOUT TECHNIQUE (ALWAYS HEURISTIC METHOD) ...... 142 4.2.1 Heuristic CRAFT (Computerized Relative Allocation of Facilities Technique) ...... 142 4.2.1.1 Input...... 142 4.2.2 ALDEP - Automated Layout Design Program ...... 144 4.2.2.1 Example ...... 144 5 COMPUTER-ASSISTED LAYOUT USING CAD ...... 145 09. Introduction to Process Plants ...... 146

1 CLASSIFICATION OF PRODUCTION SYSTEM ...... 146 2 PROCESS PLANTS – GENERAL FEATURES ...... 146 EXAMPLES ...... 149 2.1.1 Example 1 ...... 149 2.1.2 Example 2 ...... 150 2.1.3 Example 3 ...... 152 PROCESS PLANTS – GENERAL FEATURES ...... 153 ROUGH DESIGN OF A PROCESS PLANT (CONTINUOUS FLOW) ...... 155 2.3.1 Steps of system design - case of one product ...... 155 ROUGH DESIGN OF A PROCESS PLANT (BATCH) ...... 155 2.4.1 Assumptions ...... 155 2.4.2 Steps ...... 156 2.4.3 Yearly workload NHi for production equipment i ...... 156 2.4.4 Number of hours available for each type of production equipment i ...... 157 2.4.5 Number of production equipment of type i necessary to produce the production mix ...... 157 ROUGH DESIGN OF A PROCESS PLANT (CONT. FLOW/BATCH) ...... 157 2.5.1 Evaluate the yearly costs ...... 157

3 ILLY CAFFÈ ...... 157 10. Simulation basics: introduction ...... 158

VII

Summary

1 DEFINITION OF SIMULATION ...... 158 1.1.1 Why Simulation? ...... 158 1.1.2 How? ...... 158 SIMULATION AND MODELLING ...... 159 1.2.1 What’s the meaning of simulation, then? ...... 159 THE CONCEPT OF SYSTEM ...... 159 HOW TO STUDY A SYSTEM ...... 160 1.4.1 Types of Systems ...... 160 1.4.2 Analytical vs Experimental Models ...... 160 1.4.3 Deterministic vs Stochastic Models ...... 160 TYPES OF SIMULATIONS ...... 160 2 DISCRETE EVENT SIMULATION ...... 161 DES – DISCRETE EVENTS SIMULATIONS INTRODUCTION ...... 161 2.1.1 How? ...... 161 2.1.2 Industrial Simulation - Digital Factory ...... 161 DISCRETE EVENT SYSTEMS ...... 161 2.2.1 DES – Definitions of Main Components ...... 162 SIMULATION PHASES ...... 162 2.3.1 Real System - Problem Definition ...... 162 2.3.2 Conceptual Model - Detail and accuracy of the model ...... 163 DATA COLLECTION ...... 163 SIMULATION SOFTWARE...... 163 2.5.1 Choosing the Software ...... 163 MODEL ASSESSMENT AND VALIDATION ...... 164 3 MONTE CARLO SIMULATION ...... 164 LET’S START WITH DEFINITIONS ...... 164 3.1.1 Simulation: fictitious representation of reality ...... 164 3.1.2 Monte Carlo Method: technique that can be used to solve a mathematical or statistical problem ...... 164 WHY “MONTE CARLO”? ...... 165 MONTECARLO CHARACTERISTICS ...... 165 ELEMENTS ...... 165 SAMPLING METHOD ...... 166 3.5.1 Monte Carlo Simulation (MCS) in business processes ...... 166 3.5.2 Procedure ...... 166 3.5.3 Inverse transform method ...... 166 ANALYZING BUSINESS PROCESSES ...... 166 EXAMPLE - A QUIET WEEKEND … OF FEAR ...... 166 3.7.1 Model defined for analysing simulated scenarios ...... 166

VIII

01. Introduction to production system

01. Introduction to production systems

Production (process) = set/list of activities (process) required to produce final goods or services delivered to the market by a company; production is synonym of “operation”, it’s a physical (been produced) process transforming an input in an output → which has to be sold in the market

Production system = a subsystem of the company. It uses resources as inputs – raw materials, semi-finished goods, energy, information, knowledge, etc. – to provide products and services in order to satisfy the customer needs and the objectives established by the company’s strategy; Industrial system -> machines, elements such as factories to implement a production process. Production process/cycle are related to mechanical and textile sectors. Is based on the element to do the production process. The system is part of the company. A company can have one or more production system. Ex: Cocacola has many production system. System is different from Plant. Plant sometime is used as a synonym. Each company, each industry has its way to define, we are using the general terms.

Production plant = physical plant where the production system is established

1 PRODUCTION FACTORS

Industry to transform an input in output. The second part of balance sheets are the cost of production, cost to perform production.

2 PRODUCTION PROCESS - Material acquisition, data and information retrieval - Transformation o Raw materials in components and parts o Components and parts in final products - Distribution

When we deal with production we deal with different activities: 1. activities for keeping the material, the input used 2. activities in which input are modified for creating new artefact (transformation) 3. activities for sending products to the market (B2B, B2C) throw distribution

3 PRODUCTION AND LOGISTICS Logistics: moving goods and materials, activity to manage the movement, we deal with the fact that we have to move the material; logistic can be inbound or outbound - Inbound -> Production: physical transformation, in shop, in single machine - Outbound o Procurement -> taking the material, physical resources needed for production o Distribution -> sending the goods to the market

In English we call “operation” those three activities put together.

01. Introduction to production system

4 PRODUCTION AND OTHERS INDUSTRIAL PROCESSES

Product Design -> how the product should be produced From one side, the company need engineer who design the product. Industrialization (engineer)→ a group of persons to enrol the product: “engineer process, developing new product, to design and implement” leaded by a technical department part of the company.

Then the company, after designing the product, has to produce implant in which someone will have to purchase, produce, sale and distribute.

Production: composed by person and machines able to produce the product designed In this course we don’t learn how to design the product, but we are in the meet of the intersection of the new product development (technical department) and the production & logistics (operation management); this course will study how to design a production system (not the product)

5 HOW TO DEFINE A PRODUCTION SYSTEM Elements you must have to start to design a production system, a part the previous information/definitions, are these basic elements, in particular when we have to design new plants - Production process – ASME Diagram -> type of process - Bill of materials -> type/set of materials - Cycle times / Production programs -> life cycle of the process and the product - Flow sheet - Layout - Classifications These elements are different in different industries/implants and technologies

NB: we will not become expert of certain technologies; we will learn the system in which is used a certain technology and we will have to deal with different technologies. ➔ We will see the basic classification of production system.

01. Introduction to production system

PRODUCTION PROCESS ASME – American Society of Manufacturing Engineering We use a common way to describe the process, codified sixty years ago. The American society of Engineering created these type of language

Production -> transformation

Control -> we have control what we have moved, we stop the flow and we have to check it check if the production is ok or no; it may be done by human or machines

Waiting -> sometimes we have accumulation of enough material to start the next step of the production process

Flow -> the movement of the material, the movement of the pieces of stuff.

Example of an assembly line -> we have different lines, step by step they are put together

Real production process described using the ASME (cemetery) From this diagram we can see that have two different starting point, then we have two different flows, after everything is put together and then we have two different final products.

In some points we should take decision, for example: - how to divide the flow at the beginning point and the materials in them - how to proceed when we re-put together the materials - how to distribute the rocks of the cement - how to cook the cement - how to sell the final product at the final point

01. Introduction to production system

We can use these symbol to make analyses of these production process. We have the same language used by companies.

1. Raw materials, different component worked in different way and then put together (ex: the making of a chair)

2. ex: we started with OIL, then we get different type of product such as GPL, petrol

3. Assembly based on a common material, the divided again. It is used in car making.

NB: before design the production system we have to understand the production process

TECHNICAL DRAWINGS Engineers communicate in technical drawing according to an international standard, it’s the way to have knowledge about the product, to describe the final product we have to produce

01. Introduction to production system

5.2.1 List of parts & Bill of materials

Bill of material -> list of the single parts which are composing the final product

This is a typical bill of material→ list of components elaborated by the industrial department. It is the Material Requirement Plan MRP, there we use a bill of material. In a company doesn’t exist a single bill of materials exist for one product -> the design engineer describes the product in a so called “the design of bill of material”, then in the production sector/phase it will be re-elaborated obtaining “the production bill of material”; finally, it will be produced by industrial expert

01. Introduction to production system

CYCLE TIME

After the process and the components, we need to know how many products we can produce -> we need to know the time, how many hours we need to produce.

In the cycle/production time sheet the processing time for producing one component it’s written, how much time we need to produce one single product with a specific machine; without this information we cannot calculate how many machines, hours, person we need to produce.

This sheet is elaborated by the industrial engineer (expert in a specific technology) Our exercises always start with the information of how many final products we need to produce, in real life this information is coming from Industrial Engineer The main activities are calculating the time of cycle, defining the type of materials needed and indicating the production technologies to use.

NB: time is our design variable.

5.3.1 Production program / Work order

Fase Descrizione Macchina Tempo Lavoro Attrezzature Tempo setup 10 Intestatura Intestatrice I11 30 sec 4 min 20 Tornitura Tornio A21 2,5 min Utensile XYZ 1 min 30 Sbavatura Op. manuale 30 sec. 40 Rettifica Rettificatrice XX 12 min Utensile RRR 30 sec 50 …

Normally we have components which has different production time.

PRODUCTION PLANT A production system is a physical building with pipes, operator… All these systems are called factor: it should be designed, we would calculate how many people, how many buffers we will need (ex: we need to know how many centimetres the pipe has to move)

At the end, we should be able to describe the physical production system. We have two ways to describe it: 4. flow sheet: logical schema -> non-standardized way for representing a production system; we see the trucks, the pipes but we should also know the technology behind; Often used in chemical/pharmaceutical plan 5. map of the production system: it is the so called “layout”-> the map of the production system, we can use it as a design tool, to decide how to move material, how to put things. It is a layout activity. NB: The second one is not in contrast with the first one.

01. Introduction to production system

5.4.1 Flow sheet of a production plant Flow sheet of a cement plant Flow sheet of an Iron mill

5.4.2 Layout of a production plant This is a representation of a real layout: the triangle of the ASME diagram. The arrows are representing the production flow, how we move the material. It’s a messy situation, there are many flows and they meet each other. The problem is that every day there are person moving nothing. The printing department is not near to the warehouse, it’s a problem, they have to hire two more people to move the materials. This is caused by the fact that they didn’t enrol an engineer to decide the diagram/layout of the production ➔ the solution is re-organize the entire layout There is the design of the aspect of the production plant/layout

01. Introduction to production system

6 TYPES OF PRODUCTION TECHNOLOGIES Technologies: the specific way of running the producing element

7 WORTMANN CLASSIFICATION

Description of the different industrial context, the different ways a company can work, because they are built based on orders. This classification is part of our basic vocabulary.

Customer Order Decoupling Point

- Engineer-to-Order (ETO): Here, the product is designed and built to customer specifications; this approach is most common for large construction projects and one-off products, such as Formula 1 cars. - Purchase-to-Order (PTO): Here the product is already designed, but materials for production are still not in inventory, then they should be ordered. It is then like MTO. - Make-to-Order (MTO): Here, the product is based on a standard design, but component production and manufacture of the final product is linked to the order placed by the final customer's specifications; this strategy is typical for high-end motor vehicles and aircraft. - Assemble-to-Order (ATO): Here, the product is built to customer specifications from a stock of existing components. This assumes a modular product architecture that allows for the final product to be configured in this way; a typical example for this approach is Dell's approach to customizing its computers. - Make-to-Stock (MTS); Here, the product is built against a sales forecast, and sold to the customer from finished goods stock; this approach is common in the grocery and retail sectors. (ES: Barilla and De Cecco, producers of pasta are working for MTS, supermarket)

01. Introduction to production system

8 CLASSIFICATION OF PRODUCTION SYSTEMS

Three axes or the Abell classification - The company can react in different ways to the market demand - The company can produce different quantity of product - We have different type of industries/processes -> process classification

The classification scheme, proposed in (Brandolese, Brugger, Garetti, Misul, 1985), considers three criteria drawn by the correspondent orthogonal axes. It allows describing how: - the product is made through the production process; - the company fulfills the demand from the market; - the production is managed to make the required production volume. The way the product is made through the production process, and through different production systems, is the main focus of the course, while it is clear that the process/system affects and is related to how the company fulfills … & the production is managed… A point in the tridimensional space delimited by the scheme may represent a production system. It is clear that not all the combinations of the three criteria have a meaning in practice; furthermore, some combination can be observed more frequently than others. Considering the way the product is made, it is worth providing a distinction between the production process run in a process plant and in a manufacturing plant. In a process plant, the materials are subject to a non-reversible chemical-physical transformation, so that the raw materials can be hardly distinguished within the finished product. It is in general not possible to recover the raw materials, getting back through the production process to their original physical-chemical state (in other words, the finished product cannot be “disassembled” in its components). Examples of this kind of production are the paper, cement, chemical, steel, oil and gas production, etc. Concerning a manufacturing plant, two phases are typically present, not necessarily in the same company: firstly parts production, then assembly. Differently from the process plants, in this case it is possible to identify the components; therefore, disassembling the finished product allows obtaining the parts composing the product. During parts production, the materials are subject to some change in their shape and, in general, in their chemical-physical properties in order to obtain the required part features. e.g. molding creates a shape, machining modifies the shape, heat treatment changes some properties, eventually finishing operations e.g., coating, painting …. changes the appaerance of the part. Thereafter, assembly aims at joining two or more components to obtain a subassembly, which, further arranged with other components (such as other subassemblies and/or parts), leads to achieve the finished product.

01. Introduction to production system

Different types of processes are considered to assemble products; amongst them, the joining processes, such as welding, brazing, soldering, etc., should be also considered as they enable to attach parts one to another. Requirements and challenges encountered when designing and managing the production system in a process or manufacturing plant (therein, the production systems for parts production and assembly) are quite different: this motivates to distinguish the different typologies of production systems along the course. The second criterion looks at how the company fulfills the demand from the market. The following typologies can be defined according to this criterion: - production to order; - production to stock. In the case of production to order, the company reacts to a request, namely an order placed by a customer. Production to order can be further distinguished in production to single or repeat order. In the case of production to single order, the customer order is unique, as it is highly improbable that the same product, with the same specifications, will be requested in the future. The order generally concerns a limited number of product items, sometimes only one item. It is the case of products featuring a very high personalization and specificity (ships, industrial plants, furniture built on demand as designed by an architect to satisfy the requirements of a specific customer, etc.). In the case of production to repeat order, a product is made knowing that in the future it will be requested again, by the same or other customers. This is the typical case of companies using a product catalogue, possibly quite large, but at the same time defined in terms of product features, thus in terms of the required production processes and materials. It is also the case of companies acting as subcontractor, as they supply components to other companies. The supply is provided to a certain and stable number of customers, requiring it regularly along a planned time calendar (e.g. of this case: the suppliers of components in the automotive sector). In the case of production to stock, the company produces in advance with respect to orders placed by the customers, thus the production is done based on the demand forecast and the products are stocked in a warehouse waiting for orders. In the case of production to stock, the company does not wait for customer orders, but produces in advance in order to achieve a certain availability of stocked material; this allows satisfying quickly the customer orders as soon as they are placed. Thus, when the production is done, it is not known which will be the customer that buys the products being made. In this case it is clear that the uncertainty on the typologies of products and their production volumes should be rather limited. In general, the range of product variants, and their possible personalization, are restricted. The third and last criterion looks at how production is managed to make the required production volume. The following typologies can be defined according to this criterion: - one of a kind production; - batch production; - continuous production. In the case of one of a kind production, a single, one of a kind product is made, for example: a building, a ship. Because of the singular nature of this system, the variability of production processes is quite high, and the production resources are managed in order to produce the exact production volume – i.e. quantity – required by the order. In regard to the previous classification criterion, the demand, it is worth remarking that this typology may correspond to production to order, both single and repeat. In the case of batch production, the system features an intermittent operation, owing to the changes from one product to the other (e.g. 1 batch or lot of product A, then 1 batch or lot of product B, etc.), in order to obtain the required production volume. To start the production of a new batch, machines or, in general, resources in the production system usually have to be prepared, i.e. the preparation activity is referred to as set-up. As set-up entails time and cost, as well as the products may be subject to future customer orders, the company is lead to produce a production volume higher than the volume immediately required. This way, part of the produced quantity is kept in stock and, thus, it is possible to satisfy future orders without the need to restart the production of the same product (so, saving setup time and cost). The product diversification strategy, observed in the last years in almost all the industrial sectors, has pushed to a progressive reduction of batch sizes, up to cases where it is possible to produce sequences of single items of different products. The batch production can be further distinguished in two typologies: multi model production (this is traditionally featuring big batch sizes) and mixed model production (this requires the ability to manufacture in small or very small, even unitary, batch sizes) -> this will be discussed specifically for some types of production system, as it is quite relevant for their requirements and challenges.

01. Introduction to production system

In the case of continuous production, the system is instead dedicated to the production of one single product type, owing to the high production volumes and the substantial stability of the market demand, usually expected also in the mid-long term.

9 EXAMPLE OF PRODUCTION SYSTEMS

FERRARI https://www.youtube.com/watch?v=JK0NQ-1O2pA

Notes on the videos: - style is everything at Ferrari: balancing speed and style - 250.000 square meter of industry in Maranello. - final assembly line even a wind tunnel - importance of light - weight is a problem for supercar - two different transmittions but only one driveshaft (albero di trasmissione) - integration of many subsystem to optimize the whole car - v12 660 horsepower which it necessities 5 days of work : the mark is evaluated 3 bilions euros. - they customize the option: every Ferrari has at least one personalization.

There are three building located in Maranello, but they don’t have production facilities, they have only assembly facilities (ex: the body isn’t done internally, but by Scaglietti, out of Maranello; the painting is also located in Maranello) One third of the video is about the production of the engine: Ferrari had decided years ago to focus on the performance, to keep internally as much as they can

The different type and part of Ferrari had a different assembly line; the video is focused only on the production system, the new platform created in Maranello, that we will call machine-based assembly line, and we’ll learn how to balance it; it’s one of the typical line used in the automotive industries Different machines doing the same type of operations -> departments, part of the job shop; then there is then a final assembly line, several buffer between the department but they are not using it for final stocks.

In the car manufacturing, engines are producing to stock, or assembly to order (ex: Volkswagen); while Ferrari does not produce for stock, they work to order: when they receive the order, they do some customisation for the interiors; engines are built only when an order occurred, it’s not a continuous production It’s strange to see a foundry in a factory, but it could be possible

01. Introduction to production system

- Define the ASME diagram - Try to sketch the Ferrari Layout - What types of production technologies are shown? - What types of production systems have you seen there?

Body Shop First panel Check Check body assembly

Manual Car Rivets’ insertion on Body panels Chassis the chassis assembly

Paint Shop Assembly Line Primer treatment Final painting Manual polishing Check

Engine positioning Anticorrosive Transparent layer Furnace treatment application

Foundry Dripping Check Check Road test Transmission system positioning

Engine block & head Sand removal Finishing cylinder molds

Mechanic’s Workshop Racetrack test Realization of engine Dampers Check components positioning

Valve ring in head cyclinder Engine assembly Equipment Final factory check positioning

Camshaft finishing

Saddlery Shop Saddlery products Leather cutting Ironing Glass positioning positioning

Stapling/Stitching Assembly

AIRBUS Do the same – by yourself – for the video of Airbus: - ASME - Layout - Types of production technologies and production systems in place

ILLY CAFFÈ - An example of a process industry - ASME diagram (do it for yourself) - Layout (do it for yourself) - What are the main characteristics of a process plant?

THOUGHT QUESTIONS See this video: https://www.youtube.com/watch?v=DTWnQDAhp9k ➔ Can you classify the different production processes presented in?

02. Production system KPIs and costs

1 HOW PRODUCTION SYSTEMS WORK Productional system are physical system made of factors: - Raw material - Machine - Tools - Human resources

See these videos - https://www.youtube.com/watch?v=pZ-kkiWj3i8 - https://www.youtube.com/watch?v=JCe0gDQFthw - https://www.youtube.com/watch?v=5hQEAB4p1s8 - https://www.youtube.com/watch?v=1d8ikzRm-cM - https://www.youtube.com/watch?v=Qphdx5maOek Productional system are physical system made of factors: - Raw material - Machine - Tools - Human resources

NB: it’s valid in mechanic contest, not different also in textile contest, the way of working in factory are the same

It’s important to understand that the production/manufacturing system, in which production happens, could be in different moments A production machine could be in different status, it works in different ways - Working -> it is working for some hours/minutes - In setup / changeover -> we are preparing/programming the machine for work (ex: charging the materials) -> the machine is not working - Waiting (idle state) for pieces / for operators / for interventions -> the machine could be prepared but it may be there waiting for an operator, a material… (ex: without an operator with its specific action, the machine could not work) NB: the employees/operators interact with the machines in the system, and we also have to decide how they work with the machines - Blocked for breakdowns -> it should be solved - Under maintenance / repair When we are designing a system and we have to decide how many machines we need, we have to took into consideration also the times when the machine didn’t work, it has a direct impact on what we do

An operator could be involved in different tasks (working and not) - Working on a machine / system (e.g. manual assembly) - Preparing the production machine (setup), e.g. changing tools, cleaning, loading materials, etc. - Doing maintenance and/or repairing machines - Monitoring and supervising production - Performing quality checks/controls - Load / unload materials - … We need different person, specified in different work, with proper knowledge; we also have to took into consideration the variability of the human resources, what could be happen to them We have to “build” the factory, and for doing that we have to know how different part interact to each other, the different interactions between elements -> How the decisions are taken? How decisions are communicated? How to have a system which is working?

02. Production system KPIs and costs

- Production is handled in Work Orders (also said production orders, manufacturing orders, job orders, etc.), it is managed order by order -> the certain machine at the certain time has to produce the certain product in the certain way The work orders way to work born into the military contest. - Work orders are planned and scheduled in the production plan, and then “launched” and executed; the main topic of the production manager is how to handle/plan the production orders, with short term or long-term decision - Modifications to the production plan could happen (changes in priorities, problems, etc.) - Work Orders are moved in the production system according to the production / process cycle - Production systems can be organised with different layouts (following reference cases, such as job-shops and cells), and managed in different ways - Production resources are normally grouped in production shops / departments (with different logics, e.g. job shops vs cells) - The entire list of production resources is normally addressed as “shop floor” (in Japanese this is said “genba”) - Different layouts can guarantee different results / performances in production - Layouts are different in terms of production volume (number of products) reachable in the amount of time and production variety (number of different types of products)

- Continuous production (transfer lines) is useful for the company which has a very high volume of the same product - A single production site isn’t good for high volume production

Line and single-production are the opposite of production layout- architecture

2 PERFORMANCES OF PRODUCTION SYSTEMS It’s necessary to manage performances is for check if it is going well or not Main operational performances are normally time; they are standard, used by all companies - Lead time (throughput time, flowing time; lead = passing through): duration of time from start of production to finish [hours, minutes, seconds]; the time the customer has to wait before he could have the ordered product, or how long an order is in the company NB: lead time is a concept, but it is composed by different type of time - Setup time: the time it takes to set-up a production resource for processing a new work order [hours, minutes, seconds], in which the system doesn’t work (ex: a company send us an order) NB: time is not the only relevant performance for us - WIP (Work In Progress): the amount of material/work/inventory that is being processed in a certain system or is waiting on the shop floor [it is calculated in terms of pieces, quantity of work orders, but also time needed to finish the quantity of work orders]; they directly depend on the type of system that we are analysing - Production rate (throughput, rhythm, production capacity): number of products that a production system is able to produce in a time unit [pieces / h, products / day, etc.]; it can be calculated in terms of minutes, hours, days… NB: capacity is a long period indicator, we use rhythm/rate to define short time period - Cycle time (or production cycle): the time period elapsing b/w the exit time of the precedent workpiece and exit time of the successive work-piece from a system, the company define how production can happen by making a production cycle; it is the inverse of production rate [time / piece], when we have cycle time, we can calculate the production rate, and vice versa, they are opposite Those are general concepts that can be used in different level, different type of the system. Everything has to be specified in the contest we are.

02. Production system KPIs and costs

3 THE CONCEPT OF LEAD TIME The total Lead Time of a Work Order is the time that is necessary to perform all the activities inside the factory from the customer order arrival to the moment in which the material is ready to be delivered An order is entering in the production system. We prepared the machines, the machine can be working on another working, the time is passing while our order is in queue. Then, the product is produced, then there is the final control: the total amount of these activities is the so-called lead time

4 PRODUCTION TIME Also the “production time” is not entirely “productive”, it can be divided in different status: setup, manufacturing, waiting, control In a production line we can expect lead time lower than the other production system

May also include quality control, setting up CNC programmes, machine breakdown, waiting for repair, repair, operator breaks, quality issues, shortages of parts, detailed planning and control, etc.

A production line has a lower lead time than the other production system. We can calculate many types of indicators, related to lead time, such as: DO, DR, DP. Those are general concept which we could use in different ways, it depends from the context we are working, different production system has a different impact on lead time

02. Production system KPIs and costs

Other operational performances (indicators) - Utilisation (saturation of a certain system): ratio of effective production hours vs. available hours (production hours could include setup, available hours could include maintenance); it gives us the idea of if we are using for enough time the machines/system, how much are we using them, how much they are working; for now we consider them as synonymous. Flexibility: the ability to easily handle variations in demand mix (different types of products produced); it can be managed in many ways, ex: o how many different products it’s the machine able to produce; o how many times it need to produce another product from the previous one; o how many times we need to do a setup; - Availability: It measures the impact of breakdowns and stoppages on the time when a machine is theoretically available to be used; the exit time of the precedent workpiece and exit time of the successive workpiece from a system, it is the inverse of production rate [time / piece]; it’s a general concept, and also this one could be managed by different ways; it is used to measure the breakdown’s, stoppage’s impact

Obviously, those indicators/performances are connected in dynamic system

Processing time machine Production rate machine [min/piece] [pieces/min] 2 0,5 6 0,17 5 0,20 3 0,33

- Which is the slowest machine? B is the slowest machine, acting as bottleneck in the line; it’s taking more time than the other, it’s the slowest in the point of view the production system; it defines the machine rate (ex: you could drive a Ferrari, but if you have a truck before you, your speed will be the truck’s one) Analogy: production system in line is like a pipe - Being a line, which will be the lowest lead time? LT min = 2 + 6 + 5 + 3 = 16 minutes In this case we have a line; the total lead time is 16 minutes, given by the sum of the single processing time; each product will spend a lead time equal to 6 min in the system - Which will be the highest production rate (or throughput) achievable in such a line? TH max = TH of the bottleneck = TH(B) = 1/6 = 0,17 pieces / minutes (tempo di attraversamento) - And the average cycle time of the line? B = 6 minutes (B is a bottleneck)

For further details I suggest these videos: - https://www.youtube.com/watch?v=HiCS4QBloHY - https://www.youtube.com/watch?v=zBWgYn6GLl0 - https://www.youtube.com/watch?v=aVFF2hWy1-Y

The table highlights qualitative differences of the performance of different fabrication layouts. The exact performance varies according to the product, technology, product maturity, etc.

02. Production system KPIs and costs

4.1.1 Examples - Lead time for: o Project = very long -> Wind turbine towers can take many weeks to fabricate o Cellular = short -> APG produce gears for wind turbine gear boxes in several weeks o Line = very short -> Honeywell make controls to order and dispatch on the same day for some products - WIP for: o Project = high -> BAE Systems Naval Ships has months worth of stock of some items (pipes, lighting, etc) o Line = low -> Heineken beer don’t track bottles in their bottling hall as there is only WIP for 1-2 hours - Set-up time for: o Job shop = Long -> Some machine tools can take 5 hours to set up o Line = Variable -> Fiat body welding line moves from current model to new model without a break in production - Utilisation for: o Project = Low -> Some tooling may be required only at certain project stages o Cellular = Medium -> Similarities in products belonging to the same family allow to have quite balanced times and low set up losses o Line = very high -> PCB manufacturers stagger operator breaks to keep lines running - Flexibility for: o Project = Very high -> Babcock BES refit warships. They are also working on Heathrow Terminal 5 o Line = very low -> Electronics sector uses significant temporary labour to cope with demand variation - Availability

Distinguish between performances and operative conditions: - Performances are the result (measured against a multi-dimensional scale) of the logistic and productive process; it’s what we should know dealing with production - Operative conditions are the external and internal “context” in which this result is obtained, sometimes they can be decided by us, in some case no; they are way of working or state of a process that can influence a certain performance (ex: the suppliers’ lead time to deliver us a piece/material) They should be both taken into account, but they should not be mixed up

02. Production system KPIs and costs

- Internal performance: can be measured from inside, and we can modify it. The scrap is a measure, we count the number of scraps; it can be measured that is up to me as a company - External performance: it is measurable from the clients or customers. - Operation condition: an old machine can have impact in availability, number of products... It’s a situation that we could manage and modify, ee are free to decide if keep the old machine or to buy a new one MIN 55 NB: there is some performances relevant for us, other not

5 COSTS OF PRODUCTION SYSTEMS The main costs to be taken into account when evaluating a production system are the following: - Costs of installation (most of the time in CAPEX) - Operating costs (in OPEX) We should make an economical evaluation, this evaluation is not made of only real costs, we have also to consider figurative/opportunity costs.

Relevant costs to be considered in design decisions for a production system could be - Real costs (installation and operating costs) - Opportunistic / figurative costs (e.g. depreciation, inefficiency costs, etc.)

Installation costs can be defined as all the expenses that the company has to invest in a plant to enable production; they must be estimated in the design phase for evaluating the affordability and return of the related investment To start an industrial activity, it is necessary to have adequate financial resources (i.e. the capital) to be invested in all production factors that are necessary for creating the production capacity

Installation costs in CAPEX - Feasibility study (preliminary economic analysis of the project) - Development of the project - Acquisition of the ground; - Building construction - Installation of plant services - Acquisition and installation of machinery and equipment - Intangible cost of knowledge assets (know-how, patent acquisition, payment of royalties) - Interest payable on any mortgages or loans for investment

Installation costs in OPEX, they refer to the set of non-durable production assets and financial payable to start production, like inventories of finished products and raw materials, account receivable (deferred payment, typically 30-60 days), any cash for running start-up

Operating Costs are all costs to be sustained in a given period of time (typically one year), for the operation of the plant - Variable operating costs: which include all costs of operation that depend on the volume of production, like raw materials, components, energy, commissions due to the sellers, transportation, etc. - Fixed operating costs are independent of the production volume, and shall include all those expenses that remain the same independently from the production level, like: overhead (insurance, communication, building conditioning, etc), expenditure related to technical and administrative staff, rents. - Semi-variable operating costs are related not only to the volume of production, but also have a fixed part, independent of the volume of production

02. Production system KPIs and costs

Inefficiency costs do not correspond to a real flow of money, but rather represent a loss of opportunity (e.g. in terms of reduction in production volume and thus in income loss); they are defined as the loss of income resulting from inefficiency (of a machine or plant) with respect to a predefined standard They are typical related to stock-out, when our product is not in stocks, so we can’t satisfy the demand, we lose the possibility of gaining money; ex: Barilla hasn’t got the Pasta in the shelf, so the customer is buying De Cecco: for Barilla this is an inefficiency cost, linked to the stock out

Holding cost: there is also the risk of not selling something that is in stock, keeping stuff in shelf can be risk

Typical inefficiency costs are that one related to production management inefficiencies, like - overtime work costs - subcontractors’ costs - stockout costs -> you lose the possibility to get money from possible sells - stock holding costs -> it constitutes the risk of no selling the product put in stock - setup costs Those could be calculate/evaluate

To be defined “relevant” for the design of a production system a cost should be: - future (past is already “sunk”) - avoidable (if we do not follow a certain design / plan we do not sustain that cost) - differential (with respect to other alternative designs / plans)

ex: you have a date with a girl the day of the Champion League with your friend. The relevance of the cost is not defined by the real opportunity, but by the missed opportunity. It depends on what is relevant for us. This is also relevant in designing system, some costs can be considered as a miss opportunity

Depreciation differs from other cost categories as it is not an actual financial flow, but it is only the charge (for economic and tax purposes on an annual basis) of a cost already incurred for the acquisition of durable assets Depreciation is the process of allocating the economic value of the asset (amortization amount) along all the periods in which it is used Depreciation has to be intended as tax depreciation when it is calculated as a value to be subtracted from the company's gross margin for calculating taxes that the company must pay Due to the different taxation regimes, depreciation could be a cost relevant for the design decision (e.g. invest in a new plant in Poland, or revamp an old plan in Italy?)

6 HOW TO EVALUATE AN INVESTMENT IN PRODUCTION - Cost analysis - Revenue / savings analysis - Cash Flow analysis - Discounted Cash Flow Analysis - IRR / Payback time

7 THOUGHT QUESTIONS - Draw a graph showing the 3-axis production process classification. - What other classification criteria do you know? - Name the different layout types that exist for fabrication and for assembly. - What products are these layout types used for? Think of some examples. - How do different fabrication layouts perform in terms of lead time and WIP? State reasons for the differences in performance

03. Introduction to the design of production systems (Factory Planning)

1 DESIGN PROCESS It’s part of an integrated design approach (we will use examples of the automotive system) We are talking about companies, factories, industries; the company which is producing physical products, is composed of a group of people, acting using a “design/engineering process”, by creating and elaborating a concept/idea and put it to the market: we have a first idea which is designed step by step, by a group of people with different skills, with difference competences; then they test the idea, trying to understand if the idea works (experimental phase); when the test is done, when the idea seems to be right, you have to find the most appropriate way to design the product.

The design process is not a standard one, normally it’s done by phases (coloured boxes), and for each phase/box we could have different people working in define the single idea; it can change, we can enlarge the idea, the design work is an intellectual work. When it is defined, it will be transferred to others. Not only one guy is doing everything, the people involved are sharing information, receiving idea from the others, and if there is something that can be changed, they can ask to change the idea: the schema shows a “change request flow”. In most of the industrial process, if something is coming back, it means that something is going wrong; in the design-intellectual phase, if something is coming back it’s because somebody found out that one of the designs/ideas is not perfect; it’s not a problem, the company can improve it; in this way, if something is going bad, you can resolve it at the beginning

We are dealing with engineering design/process, in which every person is transferring his knowledge, solving the things not done well -> people knowledge is proved/checked This big process is done/characterized by many features, there’s no just one idea flowing, but many of them, in different ways; if you have to design a factory, it may be done in different ways, there are many alternatives; it is part of the design process to compare, try and evaluate the alternatives: you can test two different alternatives choosing the better one, or you should also find a third alternative

In a design process, along these different steps, are flowing information, data, knowledge, drawings, documents,

specifications…

This way of doing is the “Design approach” or “Engineering approach”, and is valid for one single product, or for example for huge production system. The designing engineering process is made of many substages, depending on how the company is structured; in some companies the substage exists, in another no

03. Introduction to the design of production systems (Factory Planning)

2 INTEGRATED DESIGN AND ENGINEERING PROCESS The main industrial process is something like this - What it will be produced -> the product design - How it will be produced -> the proper technologies - Where it will be produced -> the plan ex: in the automotive industry, when a new car has to be launched, they follow these steps: 6. first the car has to be designed 7. then the proper technology for producing the car should be identified 8. then, a new plant has to be created When VW has to produce a new car, it’s starting from the factories: “new car, new plant”

ex: in smartphones industry, when new product has to be launched, they design the telephone -> search a new

technology -> design the production plant

NB: this approach is the most general one, valid in the fully integrated industry, not everywhere ex: in fashion field, they have already established factories, they can change the design of the clothes; they don’t have to build a factory every time they launch a new product.

In the course we will deal with the industry using these three phases (1+2+3).

JUST AN EXAMPLE In an automotive industry they start from a concept of the new machine, then they design the real design of the machine; at a certain point we are moving from product to the process This is a typical example of an assembly process: car may be composed of component, and every component has to be produced/worked, and then there is the final assembly phase, in which all the components are put together

We will see when we have to take different production decisions, depending on the different resources used to produce a certain product, with some constrains; they could be decisions about: how many machines? how many people should we hire? how should we move the materials? ex: fiat 500 was launched in less than eight months, it’s the car with the lower time to market of launching; till that moment, the launching period was double. It was possible to achieve this goal thanks to the parallel actions of the suppliers, who were working in the designing production system, from designing the car, deciding the technologies and so on; in this way, they got the benefit of reducing the time, overlapping (sovrapposizionando) the designing activities

03. Introduction to the design of production systems (Factory Planning)

V.D. Bhise, Designing Complex Products with Systems Engineering Processes and Techniques, CRC Press. 2013.

03. Introduction to the design of production systems (Factory Planning)

This is valid in many contests: automotive, engine line, and this approach is used at component level and product level (ex: Whirlpool with a new dish washing machine, or smartphone) In some other type of industry, like primary industry or process industry, they worked in an integrated way, similar to our: from the design of the product to the design of the system. It may be said that, in process industry, these steps are happening in a more integrated way, and in this course we will not deal with process industries

3 PRODUCTION SYSTEM DESIGN AND ENGINEERING

TYPICAL ACTIVITIES OF SUCH DESIGN SUB-PROCESS The main activities that we should act, if we have to design a new factory, typical activities of such design sub- process (at different level of detail): 4.9. Demand planning -> how many products and how many types of products we have to produce in the plant in the next x years? A production system is existing to produce a certain number of products, and it’s very different designing a production system to produce 100 or 10000 of products -> the first starting point is how much products we have to produce; we need to know the demand of each product in the future, because it’s useful to understand the space, the employees involved and so on Demand planning is usually done by the marketing & strategy function, with market analysis; they are estimating the number of products that we will be able to sell, it as a strategic meaning and dimension ex: if I have to enlarge my production capability, should I take a new machine to put in parallel with the old one, or I have to follow another strategy? It’s an activity that should be done by different parts of the industry; for us it will be always be given from someone else 5.10. Industrialization / Production engineering -> which production technologies should be used, how should be the processing cycles? In this step we elaborate the expected processing cycle, for each product/component that should be produced in our building; it includes the set of activities, the type of machines needed, the different technologies we need…; these decisions are made by expert in that type of production and technologies expert (ex: you should choose if the component will be made in aluminium or plastics) In our cases, we know the material and the type of machines we are using, also industrialization will be given to us 6.11. Identification of production layout archetypes, based on production volumes, variety and expected performances (e.g. lines vs shops, material flows, etc.) We should identify the best layout for producing our products, with the chosen technologies and the constrains of the system we have; We have to make hypothesis on which should be the best layout, starting from production archetypes (job shop, flow shop, manufacturing cells), then we study the possible solutions, testing the different archetypes; we don’t start with an only idea, we are searching the best one from some This design is done for different level of detail, from the type of production in this phase, till the single working station, in the last phase

03. Introduction to the design of production systems (Factory Planning)

7.12. Workload dimensioning and definition of the number of resources 8.13. Design of the production areas, stations, machines and services (including ergonomics, working conditions, safety, etc.); we should define the specific working station/place, till the time in which I decide the dimension of each stations

NB: these points are not in sequence, it’s not done step by step, because it’s a design process; we can return back to a point, the points can be re-executed, increasing the detail of your engineering; 3-4-5 points are relevant to us The design is done in an iterative and recursive way, proceeding step by step in the detailed definition of the resources; designing is like “conducting a study”, we make an evaluation starting from our hypothesis

Main phases are - Feasibility plan (technical and economic), with the identification of the places and areas for installing the production system, as well as of the main type of solutions (layout archetypes); we design the project with calculation and specifics, in order to have later a formal acceptance of the plan; it means evaluate, writing a document, sharing this document with the board of the company, external authority - Approval (investment analysis, normative, regulations, etc.); when the plan is feasible/approved from an economic/juridical part, we start with the design implementation; it has also to be approved by the stakeholders, by every point of view - Detailed design of the system (resources, services, providers, detailed layout, etc.) - Construction and installation - Testing and launch In the real life those points are done step by step; often we will focus only on the last two/three steps

3.1.1 Terminology The process of production system design can be described by different terms - Production design and engineering - Plant design: how many machines? How many people? How many square meters? - Manufacturing engineering, Manufacturing planning - Factory design and engineering, Factory planning - … In the next slides we will often use “Factory Planning”; different methods can be used, they are normally called “design/engineering/planning models”; in industrial contest there is not difference between engineering and designing

4 FACTORY PLANNING MODELS FRAMEWORK

We have to take decisions on how a factory should be designed; (factory planning is the common way of saying) From the pictures we can see that everything is connected; there are three main perspective that we should consider, considering that each of them is linked to the other two

03. Introduction to the design of production systems (Factory Planning) ex: capacity is linked to the layout perspective: when we are deciding how many machines-resources do we need, we have to consider the workload: it’s the total amount of the products we have to produce with the production system we are design

- Capacity planning: measured in pieces in a certain time unit; it will be based on the workload estimation Capacity is used for “pieces per months/year”, but we use rate to use “hours, days”; capacity estimation is one of our activities; - Layout: in the sense of “how the machines could be disposed in the space in a logical point of view”; we have to understand which is the best archetype to use in order to have the best capacity, using the reference archetype (line, job shop); we are able to calculate the capacity for a certain type of layout, but if this will change, also the capacity calculations will change We already know the different type of layout we could use - Material flow: how the production flow could be, how I physically move the products We have to know which material I’m using and how the material should be moved from one machine to another; materials are fundamental to plan a factory We will not deal with this, it’s a subject related to the logistic course. It includes the Facility Layout and the Material handling system

NB: everything is connected, we can return back to a decision; we will have a starting point, but we could pass from it in different times Capacity Material Flow Layout During the years, many Stationary WorkLoad Analysis Mat. Flow Analysis Mat. Flow Analysis deterministic models Linear programming Linear programming Linear programming methods were invented to Stationary Queue network Queue network --- take decisions for each aspect stochastic models Markov models Markov models Dynamic Simulation DES Simulation DES Simulation DES in different ways deterministic models Dynamic stochastic Simulation DES Simulation DES Simulation DES - Deterministic or stochastic models - Stationary or dynamic

5 FROM PROCESS PLANNING TO FACTORY PLANNING - From the sequence of operation of transformation (process/production cycle) that realize a product with a defined technology process, the tasks, fixtures and materials are assigned to a workplace (machine, operator…) ➔ Material handling design (we will not deal with this activity) - Workplace are available in the space to execute the process (factory/plant layout) ➔ Facility layout planning - Timing for each workplace are defined based on the capability of the workplace (machine, fixture, etc.) ➔ Workload balancing

04. Design of Manufacturing Systems – Job Shop

6 OUTLINE - General features - Strengths and weaknesses - Examples - System design

ex: we have to build a factory to produce for the next five years wooden tables using a typical technology; we use normally two main type of production process: cutting process and glowing. Then, you should decide how would you organize the production system: we can separate the machines: in one part of the building the cutting machines, and in the other the glowing machines -> we are organizing the production system according to the kind of technologies; we are using areas/shops with the same technology, doing the same work in each of them: we called them job shop, because we organize them according to the job that has to be done It is the most way of doing around the word, its best benefit is that it’s simple to be deigned

7 JOB SHOP – GENERAL FEATURES In a job shop machines are grouped on the basis of technological processes involved (similar machines in the same department); you are planning to have a certain space for a certain type of technology Each product(*) has its own routing in the system (another way to say the process cycle) (*) Product and part are terms used as synonymous during this course

Machines of type A which do the same things with the same technologies are in one department; in this way also machines B, C… We can have different number of machines, for each department, it depends by the volume and how fast is the single machine, its speed, which depends on production rate and the specific technology

There are different arrows between the departments, each of them is representing a certain type of product and its own production flows (ex: the red product has to pass throw A, B, C, it doesn’t need D, E. The red flow for A is moved to B and then to C); not all the products necessity the same flow, and not all the products need a certain type of machine

In this way we have workers and facilities for a single department, it’s just a matter of estimating the quantities With two departments is easy; with more than two is still easy to divide the departments, but is difficult to manage the different product flow through them; it’s a difficult work for physical reason, because we have to take a lot of decisions, manage a lot of aspects

Scheduling activity: - Deciding which materials should be moved to which machines/department - How the material should be moved - Waiting time, waiting list

In particular, it’s difficult to be managed in the case we have a big volume of products (upper limit, the productivity we can achieve) ➔ The job shop is not the only solution of production process, it is good only when we don’t have huge volume

04. Design of Manufacturing Systems – Job Shop

7.1.1 Layout(*) and organisation of resources in the plant The production system results from grouping machines based on their homogeneity in terms of technological processes. It is also named as a process layout, as expression of this grouping criterion (layout per process). Equivalently, it is seen also as a set of different production departments where each department is a group of machines that can provide the same technological capability (depending on the technological process these machines support). The departments are indicated also as functional departments, remarking the fact that there is a functional separation in different production departments within the system (e.g., in a mechanical job-shop, one dept. is providing a turning function, one dept. a milling function, etc.) (*) Plant layout refers to the physical configuration of a manufacturing system/plant; in particular, it is concerned with the arrangement of available resources (…) inside the space available in the factory.

7.1.2 Products, processes and product routings Grouping machines according to their technological capability corresponds to enabling the possibility to produce different types of products with different product specifications. When a product is introduced in the product portfolio of the company, a production process has to be developed; the technical office is then in charge of process development/process planning which means some activities. The activities are (roughly speaking): - defining the process plan of the product – i.e. the operations and sequence of operations to be performed inside the plant, forming the process plan – and correspondingly - looking for the different technological processes involved in the job-shop, then identifying how the process plan is released based on the technological capabilities offered by the system; - this affects the material flows because the functional departments – that should be visited according to the process plan – may be potentially different in terms of process plans required by the different types of products (and in different order due to the sequence of operations) -> this leads to the possibility of a different (technological) routing through the plant as characteristic of each product. Overall, respect to the production system, material flows are intertwined depending on the product portfolio offered to the market. They are also variable through time depending on the market demand.

7.1.3 Product routings and logistics in the factory In a job shop, materials are moved according to the required product routings (i.e. from one department to another). The logistics (material handling through the factory) is characterized by high flexibility.

Product routings are supported by proper transport means: such transport means are flexible in the routings as they enable different material movements. E.g., a hand cart forklift (manually guided, possibly powered by electric motor) can be used for handling materials from one functional department to another, as required by product routings. The job-shop is then characterised by a high material handling flexibility (i.e. «the ability to move different products efficiently for proper positioning and processing through the manufacturing facility», as theoretical definition). More precisely, the materials are moved according to transfer lot sizes (i.e. number of work pieces per lot) which are physically correspondent to / limited by some supporting entities (e.g. pallets, bins). E.g.: pallets are moved through hand cart fork lifts. In general, these entities (e.g. pallets, bins) are used to load the transport means and inter-operational buffers where the material is temporarily stocked, waiting for the resource availability for next operations in the process plan. As such, the buffers are stock holding points carrying out the so-called decoupling functionality (b/w departments). In a job shop it is common to identify inter-operational buffers, either within each department or, more commonly, as production system buffer between the departments; the latter case guarantees a more economical solution to achieve the same decoupling functionality (indeed, the buffers are common space -> this results in less space required due to an aggregation of space requirements from different departments …i.e. advantages of «centralization» logic of the decoupling function).

04. Design of Manufacturing Systems – Job Shop

7.1.4 Human resources and organisation of resources in the plant In a job shop the labor is divided in departments according to task specialization: workers are skilled on the basis of technological processes involved.

Grouping machines in functional departments (homogeneous for technological capability) leads to a functional separation. It allows expertise to be pooled (per function): it creates a favourable condition to support knowledge transfer between workers operating in the same department. The learning process can speed up, within each department, through workers with higher competences / experiences who transfer knowledge / practical suggestions based on common problems (homogeneous for technological capability).

8 STRENGHTS High flexibility - Short to medium-term flexibility o Mix o Volume o Product (customization) - Medium to long-term flexibility o Product (innovation) o Expansion

Thanks to basic flexibility in the production system: - Machine flexibility - Material handling flexibility - Routing flexibility

Subsequently: - Low impact of breakdowns - Low obsolescence of the system

FLEXIBILITY A fundamental strength of the job-shop is its high flexibility (in the usage of technologies) A job shop is flexible, because - You can produce every product that you want (obviously if they need only the technologies you have) -> mix flexibility, it’s flexible in the type of production - ex: for Ferrari, the creation of an engine is a Job shop, consisting in mechanical departments with different type of machines -> the capability for building engine is in their mechanical department. - You can produce high volume; if the demand is increasing and I need more hours in the department A, I can increase the number of machines (if there is space in the building), I don’t need to change all the system;

8.1.1 Definitions (conceptual) Flexibility is defined as «the ability to change or react with little penalty in time, effort, cost or performance (e.g. quality)»; in relationship to this definition, the concept of «range» should be also defined, that is more precisely the «range of possible reachable states» (e.g. operations, positions): therefore, changes or reactions are enacted from one state to another state within a reachable state space. E.g. 1 a range of products / operations that a machine can execute; considering this machine-level, products / operations can be changed within the range with limited cost / time to switch (from one production order to another). Changes / reactions can also lead to modify, at some extent, the reachable state space. E.g. 2 a range of products that a plant can execute; considering this plant-level, within the range of technological processes involved in the plant, new products can be launched / introduced with limited cost / time / impact to launch (thus changing, at some extent, the range of products offered to the market).

04. Design of Manufacturing Systems – Job Shop

This general notion of flexibility can be applied using different approaches: economic, organizational, operational, strategic approach. Considering the operational approach, we focus on the flexibility that can be guaranteed by the manufacturing system (manufacturing flexibility). Manufacturing flexibility is «the ability of a manufacturing system to adapt to changes in environmental conditions – market’s demand such as, e.g., different production volumes required by the market – and products and processes requirements – variability of their requirements such as, e.g., different product specifications + different sequences of operations (process plans) required for different products, …. Overall, the request for flexibility is higher with: - a higher variability of the demand; - the shorter life cycle of products (-> changes in requirements); - the wider range of products that the business aims to offer to the market; - the increased customization of products; - the shorter delivery times to fulfill an order (this may be however a problem as we will discuss later, concerning the lead time through a job shop). Based on such requests it is clear that flexibility can be defined on a temporal basis, i.e. classified according to the temporal horizon where flexibility is effectively exploited. The job-shop shows relevant strenghts in regard to the manufacturing flexibility, both for what concern the short/medium and medium/long term.

8.1.2 Different dimensions Different dimensions can be now defined for flexibility. Considered, in the remainder, the main dimensions where the job-shop shows relevant strenghts. - (Short/medium term) Mix flexibility can be defined as the «ability to meet the market’s requirements in terms of variety of products supplied in a certain time»; e.g. it can be measured as «wideness of the range» of products / product types. Volume flexibility can be defined as the «ability to deal with variations in the aggregate demand», e.g. measured in relationship to the variation of the production volume required by the market. - (Short/Medium/long term) Product flexibility can be defined as the «ability to meet the demands of the market in terms of product specifications» (in a certain time, i.e. also short term) > product modification / customisation; + the «ability to vary in time the production mix» (i.e. «ability to deal with additions or subctrations over time») by launching new products > product innovation (medium/long term). Expansion flexibility can be defined as the «the ability to easily add technological capacity and production capacity» in the production system.

8.1.3 Mix flexibility A job-shop can produce a wide range of product types + can frequently change the mix over time in terms of relative production volumes (of those product types), i.e. % respect to the total production of a given mix in a certain time (Mix Flexibility). This is possible because the job-shop is not constrained to a unique product type, thanks to different characteristics that can be found in a job-shop, primarily: - machine flexibility (the «ability to process a variety/range of different parts effectively», in other terms «the ability to perform various types of operations w/o requiring a prohibtive effort in switching from one operation to another»; all in all, the machine is not dedicated to a single product, but flexible to product change overs, @ some cost / time / impact (****)) - material handling flexibility («the ability to move different products efficiently for proper positioning and processing through the manufacturing facility»; material handling not rigid, not constrained to the product routeing of single products / single group of products, but flexible to different product routeings (******)). - With special concern to changes in relative production volumes (in the mix), routeing flexibility is particularly relevant, that is: the routeing flexibility within each functional department (the «ability to process a given set of parts / products on alternative machines»; not just one machine possible for a required operation, but flexibility on the alternative machines that can be visited; worth a remark: not necessarily all the machines can be visited, some could be not visited due to some constraint e.g. required vs. available workable volume) and - routeing flexibility through / betweeen functional departments (the «ability to process a given set of parts / products based on alternative technological cycles / process plans»). In fact, routeing flexibility is

04. Design of Manufacturing Systems – Job Shop

then a lever to cope with variations of the machine workload induced by variations in production volumes (rebalancing the workload …) (***********). (****) not necessarily a machine installed in a job-shop is highly flexible; this depends on a design choice in regard to the type of machines selected for the system; more the machine is a general purpose type, more its range of products / operations is wide; this is of course possible due to the technological features of the machine. (******) this is a clear characteristic that can be naturally associated to the job-shop system: by definition there is no rigid interconnections, ultimately guaranteeing different product routings (adapted to the processing requirements of different products). (***********) it is worth remarking that the material handling flexibility enables / habilitates the routing flexibility as direct consequence

8.1.4 Volume flexibility A job-shop can cope with variations in the aggregate demand (Volume flexibility) thanks to the same reason: - routeing flexibility within each functional department - routeing flexibility through / betweeen functional departments

8.1.5 Product flexibility Product flexibility regards the new product launching after product innovation or customization. A job-shop can facilitate the introduction and engineering of new products / customized products w/o affecting much the production of product types already in the portfolio. This is possible thanks to different characteristics that can be found in the job-shop. New products / customized products can be launched thanks to characteristics previously discussed: - machine flexibility (….); - material handling flexibility (…) - it is worth remarking the decoupling functionality of different system buffers & the fact that machines are decoupled as well within a dept., which facilitates the concurrent production of new products / pre- series and products already existent in the portfolio) Moreover, it is worth remarking the benefit of routeing flexibility within or b/w functional departments, which can be a lever also to reduce the impact of new product launching (i.e. for some production period, some production capacity of one or more dept. should be dedicated to produce pre-series/trial production; hence, the production of product types already in the portfolio is continuing with some reduction in production capacity due to pre-series; routeing flexibility can be used to rebalance loads on the machine and thus to limit the impacts of pre-series/trials, if needed).

8.1.6 Expansion flexibility If more production capacity is required, because the demand is growing (i.e. more work-pieces required per day, as long term growth), more machines are required and can be installed more flexibly in the job-shop; at the end, this leads to more production volumes that can be produced. This is possible thanks to different characteristics that can be found in the job-shop, such as: i) material handling flexibility (not rigid, not interconnected rigidly the machines > layout can be re-arranged by adding machines, w/o much or no intervention at all on the material handling system). In this specific regard, a proper layout planning is required as pre-condition for expansion flexibility: in particular, re-arranging layout through the installation of new machines is possible if there is sufficient space for including new machines (i.e. sufficient space for new machines was included when the facility was built considering rooms / spaces for future capacity expansion). Extending the concept, the installation of new machines of different technological capability is also possible (i.e. sufficient space for new machines/technologies was included when the facility was built considering rooms / spaces for capacity / technology expansion). Adding technologies bring then additional benefit in terms of product flexibility, as the range of operations – possible thanks to the newly available technological capabilities – is potentially growing (i.e. as concept, changing the range of reachable states). An overall advantage from the financial point of view of the characteristic of expansion flexibility is that the investments are progressively required, by adding new machines / technologies according to the demand growth.

04. Design of Manufacturing Systems – Job Shop

FURTHER STRENGHTS - low impact / vulnerability to breakdowns (short-term) - low obsolescence (long-term) of the job-shop can be seen as a consequence of flexibility.

Thanks to the flexibility of the shops shop, this kind of production system has other two strengths: - If a machine of a kind is not working, the job shop system is less subject to break-down: we have other machines able to do the same action, we have more option; it would be difficult if a single machine has to do everything -> job shop is more available - A system like this has less risk to become obsolete; over the year we should change the machines, using old and new machine at the same time; in this way the department is still able to produce what the market is requiring, because there are both new and old machines ➔ It’s the most used production system used around the world

8.2.1 Low impact of machine breakdowns The production system is less vulnerable to a machine breakdown: the production capacity is reduced, but with a partial impact on the total capacity that is nominally installed. This is possible thanks to different characteristics that can be found in a job-shop, primarily: i) routeing flexibility within & b/w each functional department are flexibilities that are a lever to reduce the impact of a machine breakdown (rebalancing loads, by deciding some alternative routes through machines given the process plan, or even alternative routes through different process plans, in order to reduce the impact). Moreover, it is remarkable the role of buffers as they are structures that decouple the operation of machines through stocked materials as well as available capacity to stock materials > the decoupling functionality due to these inter- operational buffers – containing high WIP – largely avoids the possibility of a propagation of a machine breakdown to other machines; therefore, other machines do not stop because of material starvation or blocking; in fact, material is available from WIP, or there is room / stocking capacity for material still available in a buffer.

8.2.1.1 Obsolescence – short introduction of this concept It is worth shortly introducing the concept of obsolescence and some related issues. Ageing is a related issue but it is not obsolescence. More precisely, ageing is due to the use of machines and their degradation through time; it can be seen as an endogeneous factor – endogeneous to the plant – that characterizes each equipment / machinery life cycle; nonetheless, it is not the only factor (i.e. not enough) to define the concept of obsolescence. Obsolescence is defined only after considering some exogeneous factors due to market needs and opportunities. In particular, equipment / resources / physical assets may be still adequate (i.e. not aged + capable to provide performances); nonetheless, the market demand could not be requiring their «functions» (i.e. the outputs that is produced / offered) or there may be available more convenient, new technologies (more cost-effective): these two exogeneous factors are leading to the obsolescence of the existent plant. E.g. estacion mapocho / santiago; formerly used as train central station > but … reduced demand for travels, travelling by train was not working in Chile > «functions» not required by the market > obsolete even if not aged > (to continue the story …) the train station was then revamped to offer a new space / facility for new functions > exhibitions / museum > costs for life extension, contrasting obsolescence by adaptation to new functions required by the market …

8.2.2 Low obsolescence of the production system The production system is less subject to obsolescence primarily because it can adequately cope with the following (exogeneous) threats: i) shrinking demand + changes required in functions of the production plant (i.e. the plant should be used, according to the market’s demand, to produce different ranges of product types, variable over time); ii) technological development. This is a natural consequence of different characteristics that can be found in a job-shop. In a general sense we know that job shop has a high mix flexibility (range of products is wide, the system is not dedicated to – so not dependent on – the demand of a single / few products) -> Grounding on this charateristic, and reasoning on a long term, it is the product flexibility («ability to vary in time the production mix») that reduces the risk that the system becomes obsolete. Besides, the expansion capacity allows to include new technological capabilities, new machines with a technological capability at the state of the art.

04. Design of Manufacturing Systems – Job Shop

9 WEAKNESSES - Limitations in efficiency (machine efficiency) - Qualitative characteristics of the product can vary for different pieces In a job shop we have products that is running in departments where there are machines with different ages, so it’s also difficult to find where we have qualities problems, it’s difficult of taking process quality under control; maybe, some WIP are older, because the products can stay in the system for a long time - Production management is difficult o High WIP: there are many products which are running throw the machines o Lead times are long (because of queues) and characterized by high variability 2a 2b o Difficulties in estimating delivery lead times o Low utilization rate of machines: it is difficult to saturate the machines; we have to satisfy lead time, order time, and the objective is not to saturate the machine. It can be not a problem, if the cost of the machine is low; if the machine costs 1 millions of euros, not saturating the machine it’s a problem, so you should try to saturate or find another solution instead of the job shop; other layout will help us to overcome these limits

Moving the material can be difficult; if we have hundreds or thousands of products, organized in thousands of orders, which should be moved every day, it is difficult to avoid long queue, long wait in the corridor. Being planner of the system is complex: in the daily activity, you should take decision of the single machine and single operator, you should plan something that will have its effect in the long terms Production and planning in job shop are a difficult work in medium-long term, because you have to take decision of hundreds of machines, products, materials, person, actions; it’s a heavy work in which there could be problems. We called this activity scheduling: it’s not only deciding which material has to go in a certain machine; we have also to plan, for example, the area in which we have enough square meters to wait in the queue. Waiting time are normally happening in those systems, because it can happen that all the products need the same department in a certain moment, so it is difficult to be managed; in particular, in the case of many different kind of product: if we have three products is easier, if we have thousands of products or the same product with different features, is very difficult. ➔ The upper limit of the job shop is link to the productivity and volume that it can succeed.

A typical job shop is used to produce products as much as possible in time, not with the highest quality. It is difficult to calculate production capacity that depends on - Mix of jobs that have to be manufactured - Technological characteristics of jobs - Complexity of pieces to be manufactured - Possibilities to use alternative routings - Number of machines and their state - Lot sizes - Ability to schedule jobs

RELATIONSHIP B/W FLEXIBILITY AND PRODUCTIVITY Flexibility causes penalties in time, effort, cost or performance (also quality) > overall, then Productivity (Y/X) is reduced. That is, e.g.: an high working time nominally available (a high number of working hours) is required as input (X) in order to achieve the required output (Y), i.e. target production volume. Some reasons can be discussed. - (r.1) Routeing flexibility within or b/w functional departments often corresponds to the fact that the group of machines that can provide the same technological capability can provide it with different performances o E.g. 1 quality characteristics of the processed products can be different, because tolerance guaranteed by different machines could be not the same in the job-shop > overall, less quality yield, high scrap rate or reworks … > in general, qualitative characteristics of the products can vary for different work-pieces when changing the machines where the product is processed, 2a

04. Design of Manufacturing Systems – Job Shop

vs. 2b; -> subsequent effects on quality + machine efficiency (non efficient use of machines) > more hours needed to achieve the good production > reduced productivity. o E.g. 2 the cutting speed (in a metal cutting process) could be not the same in different machines, even if the technological capability is the same > possible drawbacks in resulting performance (production rates) > reduced machine efficiency i.e., less efficient use of production hours (with lower speed) > more hours in order to obtain the target production volume > reduced productivity - (r.2) Machine flexibility means the possibility to switch from one product/operation to another, but this corresponds to set-up time -> less hours used for processing products/materials -> non efficient use, reduced efficiency of the machine working time (i.e. machines used to make setup) -> more hours required to obtain the target production volume > reduced productivity

PRODUCTION MANAGEMENT IS DIFFICULT Scheduling is complex because of three main reasons. - (r.1) Whenever a portfolio of product orders is planned for a given period, scheduling aims at deciding when the orders are loaded (loading/timing), how orders are sequenced to be processed at different machines (sequencing), which alternative process plan is scheduled for each product (product routing) >>> this is a combinatorial problem, and its complexity increases with the high number of machines, the high number of product types/orders, the high number of alternative process plans for each product. - (r.2) Scheduling is a multi-objective decision making problem, with objectives which are often conflicting (in trade off), e.g. increasing the utilization of machines (i.e. utilized for processing work-pieces) may be obtained by minimizing the set-up times; but this decision may be not aligned with the need for some production orders to guarantee their delivery reliability with respect to the planned due dates (i.e. delivery before or by the due date > minimize tardiness). - (r.3) On-line control and scheduling (during production advancement) is required to cope with different types of unexpected events, happening in the job-shop. On-line scheduling brings to changes during the production advancement, required to cope with the perturbations caused by the unexpected events.

9.2.1 Effects of this difficulty are resulting in subsequent performances WIP is kept at a high value with the objective to avoid that machines are waiting (in standby) for reason of material starvation. Primarily, this is a direct consequence of the difficulties in production management: on a short time, the production schedule of the queues in front of the machines / the re-schedule with unexpected events during production advancement leads to define a target WIP (to be kept in the system) which is high; this «solution» is a kind of protection, and it eventually has the effect that machines can be sufficiently fed up with materials and utilized, notwithstanding the complexity of the scheduling problem. The drawback of high WIP is high manufacturing lead times LTs: due to the number of production orders present as WIP in the system, every time an order has an operations which requires to visit a machine, it meets a relevant number of orders already waiting to be served by the machines, hence an high queue in front of that machine. High queuing times leads to high manufacturing LTs. The difficulties of scheduling production orders, expecially related to the changing production mixes and intertwined material flows, overall would lead on a short term to achieve a dynamic variation of the workloads in different machines: hence, the bottleneck machines (i.e. the most utilized) are changing as a consequence. This has two further consequences: - queuing times are changing (more WIP, more queuing times in front of the bottlenecks) > manufacturing LTs are changing > it is then difficult to estimate accurately the delivery lead times to a client (that can be also the production department downward, i.e. client workshop) > difficulties in guaranteeing high delivery reliability (i.e. meeting the due dates) and in the use of management system which assumes knowing the lead time to plan in respect to some dates (i.e. MRP); - some machines are underutilized in some short term period (low utilization rate). o Some standby of the machines, waiting for an operator making auxiliary operations on other machines, may lead to reduced time effectively available to produce -> standby. o Even if WIP is high, there is still a risk of material starvation when an high number of production orders is queued up in front of bottleneck machines (in other words, the machine is underutilized due to other machines – the bottlenecks, i.e. external cause) -> underutilization due to standby -> as I cannot cope with a good schedule of machines -> scheduling inefficiency;

04. Design of Manufacturing Systems – Job Shop

9.2.2 Weakness in the system design This weakness is related to the design / planning of such a system: it is difficult to calculate / estimate the production capacity available from the machines installed in the job-shop. The following factors motivate the difficulty. - Production mix: changes in the production mix (during time) → changes in the machine workloads → changes in the utilization rates of machines → different bottleneck machines > different production capacity available from the system. - Technological characteristics of jobs / complexity of pieces to be manufactured: different process plans / sequences of operations, different requirements in terms of working / processing times … → changes in the machine workloads → changes in the utilization rates of machines → different bottleneck machines > different production capacity available from the system - Alternative routings: changes in the process plans / product routings (b1) → changes in the machine efficiency (i.e. less productivity, more resources needed to achieve the target production volumes) > changes in effective / actual workloads at some machines + (b2) possibility to rebalance workloads (i.e. some degree of freedom in design choices) b/w machines, in order to reduce workloads at bottlenecks → overall, (b1) + (b2), changes in the utilization rates → different bottleneck machines > different production capacity available from the system - Number of machines and their state: if some machine is not available, there is a reduction of capacity of a functional department → difficult to estimate the overall effect on the production capacity of the system (combining, for ex., with the choice of alternative routings after the capacity reduction due to breakdown) > different production capacity available from the system - Lot sizes: changes in the lot sizes (i.e. sizes of the production orders / jobs) → changes in the number of set-ups required (to change production orders / work-pieces in order to finally produce the target production volumes) → e.g. increasing lot sizes = savings number of set-ups and total set-up times, hence less effective / actual workloads, higher utilization rate (for real processing) > different production capacity available from the system > better utilized - Ability to schedule and control production orders / jobs: see previous discussion on scheduling complexity → dynamic bottlenecks, underutilization of some machines (in stand-by) → lower utilization rate caused by inadequate scheduling > different production capacity available from the system > worst utilization due to not adequate schedule - Lot sizes + Ability to schedule and control production orders / jobs: (when set-up times are sequence dependent) changes in the sequencing policies → changes in the set-up times and hence utilization rate (for processing) → e.g. savings set-up times with adequate sequencing policy > different production capacity available from the system > depending on more or less optimized sequences (on the minimization of set-up times or not) The real dynamics of the system is a combination / superimposition of all these conditions > this leads to difficulty of estimates of production capacity.

04. Design of Manufacturing Systems – Job Shop

9.2.3 Example 1

9.2.3.1 Metal processing / working In the process plan of a product, we will have a sequence of operations, needed to achieve the required product features according to specifications. Operations are planned considering the technological capabilities offered by the job-shop, and having initially roughing operations, in which the machine tool removes high volumes of metal quite rapidly, and finishing operations in which the machine tool removes comparatively little metal. The technological capabilities depend majorly on the machine tools’ characteristics (e.g. workable volume) and the cutters equipping the machine tools. - Brief description of the processes (see below some descriptive notes in the annex) - Brief description of the layout and possible material flows through the layout (i.e. non-linear and crossing through different shops, intertwined) as effect of different process plans / products - Expansion of the layout, probably progressive through years > for example, one can guess that standalone, general purpose machines (i.e. CNC machines) were added later in a separated part of the plant > expansion of capacity and integration of some automation (i.e. technological capability) in general purpose machines - More focus on the manual fabrication system whose operations are summarized in the list of technological processes and applied to the layout considering the presence of machines that can operate the technological processes; remark # 1: turning is not separated neither according to processes – internal / external turning – nor to levels of automatic control of machinery – automatic lathe and manual lathe – - Quality control has a separated room in the layout (“collaudo” separated from technological processes)

9.2.3.2 Annex Some short descriptions taken out (also partially) from http://www.britannica.com/ (e.g. http://www.britannica.com/EBchecked/topic/382939/milling-machine)

9.2.3.3 Turning (external / internal) - A Lathe is machine tool that performs turning operations in which unwanted material is removed from a work-piece rotated against a cutting tool.

04. Design of Manufacturing Systems – Job Shop

- The lathe is one of the oldest and most important machine tools. Wood lathes were in use in France as early as 1569. During the Industrial Revolution in England the machine was adapted for metal cutting. - Internal turning is known as boring and results in the enlargement of an already existing hole. For internal turning on solid work-pieces, holes are drilled first. See also boring machine; drilling machinery.

9.2.3.4 Milling machine - A milling machine is a device that rotates a circular tool that has a number of cutting edges symmetrically arranged arout its axis. - The work-piece is commonly held in a vise or similar device clamped to a table that can move in three perpendicular directions. - Disk- or barrel-shaped cutters are clamped through holes in their centres to arbors (shafts) attached to the machine spindle; they have teeth on their peripheries only or on both peripheries and faces.

9.2.3.5 Sawing machine - A sawing machine is a device for cutting up bars of material or for cutting out shapes in plates of raw material. - The cutting tools of sawing machines may be thin metallic disks with teeth on their edges, thin metal blades or flexible bands with teeth on one edge, or thin grinding wheels. - The tools may use any of three actions in sawing: true cutting, grinding, or friction-created melting.

9.2.3.6 Welding machinery (from http://en.wikipedia.org/wiki/Metalworking) - Welding is a fabrication process that joins materials, usually metals or thermoplastics, by causing coalescence. - This is often done by melting the work-pieces and adding a filler material to form a pool of molten material that cools to become a strong joint, but sometimes pressure is used in conjunction with heat, or by itself, to produce the weld. - Many different energy sources can be used for welding, including a gas flame, an electric arc, a laser, an electron beam, friction, and ultrasound. While often an industrial process, welding can be done in many different environments, including open air, underwater and in space. Regardless of location, however, welding remains dangerous, and precautions must be taken to avoid burns, electric shock, poisonous fumes, and overexposure to ultraviolet light.

9.2.3.7 Grinding machine / grinder (normally a finishing process) - A grinding machine, often shortened to grinder, is any of various power tools or machine tools used for grinding, which is a type of machining using a rotating abrasive wheel as the cutting tool. - Each grain of abrasive on the wheel's surface cuts a small chip from the work-piece via shear deformation. - To grind a cylindrical form in a work-piece, the piece is rotated as it is fed against the grinding wheel. To grind an internal surface, a small wheel is so mounted that it can move back and forth inside the hollow of the work-piece, which is gripped in a rotating chuck. On a surface grinder, a flat magnetic plate or a vise holds the work-piece in place on a table that moves back and forth under the rotating abrasive wheel. At the end of each traverse the table is moved automatically a short distance at right angles to the direction of travel. - Grinding is used to finish work-pieces that must show high surface quality (e.g., low surface roughness) and high accuracy of shape and dimension. In most applications it tends to be a finishing operation, removing comparatively little metal. However, there are some roughing applications in which grinding removes high volumes of metal quite rapidly.

9.2.3.8 Deburring machinery (another finishing process) (Sentences taken from OEM web sites) - The burrs resulting from a metalworking operation may be tolerable; however, burrs are always present. - When the engineer determines a burr must be removed, numerous manufacturing processes are available from which to choose. - An important element of this decision is the “make or buy” decision regarding the purchase, operation and maintenance of specialized in-house deburring equipment versus sending parts to a qualified contract deburring job shop.

04. Design of Manufacturing Systems – Job Shop

- Removing INSIDE and OUTSIDE “burrs and sharp edges” that are normally created during cutting operations; it is possible to “deburr” round, oval, square, rectangular tubes, irregular shaped profiles made of iron, stainless steel, aluminium and plastic materials. …

9.2.4 Example 2 Metal processing / working - Manufacturer of valves + focus on the production of valve bodies as product type - Raw materials / processed materials transported by means of hand-carts + waiting in an available space (inter- operational buffer) within the functional department + transfer lots constrained by the bin sizes → material handling flexibility - Different options to produce in different machines, with different constraints and characteristics (tolerance, workable volumes …) → machine flexibility + routing flexibility within the functional department - Task specialization of the workers → skilled to work on this type of machines, as installed in this functional department

9.2.5 Example 3

Semiconductor manufacturing A job-shop can be found not only in the mechanical sector. See for example the semiconductor manufacturing, where many conditions typical of a job shop can be identified, e.g. - different sequences of operations planned for a wide variety of products; specifically, sequences are made of many operations and include also re-entrant flows (i.e. revisiting the same machinery for next steps in the process plan), required to obtain target product specifications > intertwined material flows - material handling flexibility, operated through transfer lots depending on the required product routings + routing flexibility

Some examples - https://www.youtube.com/watch?v=gJWMCUM dO4Q - https://www.youtube.com/watch?v=V-9eMmfThD8 - https://www.youtube.com/watch?v=hWz8_KbB2t0

10 TYPICAL QUESTIONS RELATED TO SYSTEM DESIGN Given the element regarding the demand, the technologies. Then we should decide: Typical questions: what I should do to design? - How many machines do we need to meet demand? This is difficult to understand When we have this element, we have also to decide: - How many operators do we need to meet demand? - Where are the bottlenecks? The department that suffers more, in order to understand from where is coming the break-down - What happens if the production mix changes? - What happens if a machine break downs? - What is the effect of reducing setup times or lot sizes? - What is the effect of adding another machine to the system?

04. Design of Manufacturing Systems – Job Shop

- ….. these are all questions that can be answered by using the system design model presented in the remainder of this presentation) > suggest thinking to the Mechoff case + consider also that some questions stimulate sensititivity analysis (e.g. what happens if a machine break down, what happens with more preventive maintenance, what happens if the production mix changes …) with respect to a base scenario (how many machines / operator do we need to meet demand

11 ROUGH DESIGN OF A JOB-SHOP This way of doing is already codify in Rough design of a job-shop; there are more ways of doing, this is the basic

STEP 1 Production mix definition - Identify all the product types - Estimate yearly demand for each product type - Define the lot sizes for each product type

Identification of product types suffers from uncertainty / uncertain data > how to identify the product types? - Based on analogies with past experiences, similar plants / productions that a corporate has been producing + Fostering future scenarios for potential production mix - Besides, it is worth remarking that a sensitivity analysis can be useful in order to cope with uncertainty: due to uncertainty, a set of «credible» scenarios can be proven as a range to see how design decisions are changing/robust (what happens if a scenario happens?)

Lot sizes are defined for the system design; remember that this definition affects the trade-off b/w set-up costs and stock holding costs; during production management, the lot size is in fact a relevant variable as well, exactly due to such cost trade-off.

STEP 2 Routing definition - Define the main routing for each product type - If possible, define alternative routings

STEP 3 Machine identification - On the basis of routings, it is possible to identify all the machine types that are necessary to manufacture the production mix; two options: o Found the right supplier/vendor for a certain type of machine -> it could be passing a lot of months before you find the right technology you need o Build the machine by your own -> it needs a lot of money, but it’s more specific on your needed; it’s an old way of doing, popular till the 80’s, but in some business it’s still popular (ex: the electronic one which produces the tolls)

STEP 4 For each product type, calculate the total time of the operations that have to be done on the same type of machine -> 푇푖,푗: 푖 = 푚푎푐ℎ푖푛푒푠, 푗 = 푝푟표푑푢푐푡 To calculate how much machines I need, I need to know how much product I have to produce, so how much time they need to be produced; it is expresses in terms of time of work that I need, if I know the type of machine (technology) that I use

04. Design of Manufacturing Systems – Job Shop

It considers the time needed for the processing cycle on a work-piece; the cycle also includes some auxiliary movements required to position the work-piece during the processing cycle (e.g. FIDIA case / high milling machines, focus on the processing cycle); if more operations are carried out at different steps of the process plan, Tij includes the total time of these operations (e.g. case of re-entrant material flows, e.g. semiconductor manufacturing). NB: Tij does NOT include the set-up times: set-ups refer to times needed to prepare the machine for the next processing cycle, e.g. (in case of machine tools) make some machine regulation + change tools + fixing the work- piece, positioning and clamping on the machine tables (needed work holding device / system as clamping system), etc.

STEP 5

Calculate the yearly workload NHi for each type of machine i 푁 푇푖푗 ⋅ 푄푗 푆푇푇푖푗 1 1 1 푁퐻푖 = ∑ ( + ⋅ 푁퐿푗) ⋅ ⋅ ⋅ 3600 ⋅ (1 − 푆푅 ) 60 퐴푖 퐻퐶푖 푇푅푖 푗=1 푖푗 where - i = index of the machine-type - j = index of the product-type - N= number of different product-types - Tij = unit working time [seconds/piece] - Qj = quantity of product-type j that has to be produced [pieces/year]

- SRij = scrap rate (0 <= SRij < 1); - It considers the possibility that in production I can produce something that is wrong ex: if 10% of products are bad and 90% are good, I should put this fact in the denominator as (1-SR), as a safety coefficient, in order to increase the amount of needed time, because I will spend more hours doing some products because I had some scraps; in general the SC depends on the type of machine and product - STTij = setup time [minutes/setup]; it is an estimation of how many times I will change my productions/product; a typical job shop is producing different benches/batches, I have to do setups for each of them; you have to sum the STT for each product NLj = number of lots of product-type j [lots/year]; it indicates how many times I’ll change the production - Ai = availability (0 < Ai <= 1) it can happen a break in a machine, this coefficient will increase the number of hours needed because in the future I can lose hours in repairing the machines; it’s a safety coefficient - HCi = human coefficient (0 < HCi <= 1); human operators have an impact on the final results; if an operator has to upload the material, it will lose time of production. We consider this coefficient because human can lose time - TRi = trial rate (0 < TRi <= 1); its relevance depends from the type of industry, for example for the pharmaceutical industry is really important - 3600 and 60 because in mechanical engineering, production is measured in seconds (processing time) while the set-up time is usually measured in minutes; we should apply this numbers only if we are not in the same unit In a job shop we have different product j, so we have to sum the NH for each of them to have the NH for the single machine; we obtain the needed hours; we have the needed hour for producing that kind of product in that machine;

11.5.1 The coefficients are given: these indexes have been codified during the years, during the years the industry collect the data; until that estimations, we have to do some assumption and hypothesisCoefficients (measuring time losses, cfr. Turco) - SCRAP RATE SR: percentage of materials out of tolerance (not achieved the target quality); the material cannot be restored or repaired (reworked), hence it is discarded. More general, we can consider also the possibility to rework the material (which causes time loss, as well) It increases the amount of time, because I have to produce more products, it’s a safety coefficient

04. Design of Manufacturing Systems – Job Shop

- TRIAL RATE TR: percentage of time, when the machine could theoretically be used, since the technical conditions required for its use are fulfilled, but the time is dedicated to trial production (subtracted as time loss). In fact, some external reasons (i.e. external to the machine) leads to non utilization: in this case, the machine is not utilized because it is used for technical tests for trial production / pre-series; therefore, this time is not planned for production, thus leading to time losses for trials (i.e. subtraction of these time losses from the time that can be theoretically used) - AVAILABILITY: percentage of up time (intervals), when the machine is required for production and actually available to work (w/o trials), with respect to the total time (up time + down time); down time intervals regard the overall failure and maintenance downtime. In this case, the loss is caused by some technical conditions & requirements (preventive maintenance planned in the production shift > hence impacting on the required production time) + malfunctions / anomalies / failures (by definition, impacting) - HUMAN COEFFICIENT: percentage of up time, when the machine is required and actually available to work & the operator is available to carry out its required tasks. Sometimes, in fact, the operator cannot be present because he/she is carrying out tasks in other machines; as auxiliary resource to carry out tasks related to the operations of the machine (load/unload work-pieces, clamp them etc.), sometimes he / she is busy when required (in other machines); this leads to the occurence of some time losses on the machine under concern, which is then waiting for the worker; in other words (alias), the machine is waiting in a stand-by time, caused by the organization of human task allocations to machines leading to the occurrence of the problem of man-machine interference (this theory will be considered later on during the course)

➔ Applying the formula, the yearly workload NH takes into account the need to load the machines (on yearly basis). Thanks to the coefficients, NH also considers the presence of time losses within the machine calendar time -> thus leading to a gross / effective / actual workload required from the machine

STEP 6 In the real life we should also consider the impact of the yearly working availability; we have to consider also the possible lost in efficiency in the scheduling, I can lose some time for internal inefficiency in planning or scheduling Calculate the number of hours available for each machine-type i

AHi(s) = WHi(s) * SE where

- WHi(s) =yearly working time available (depending on the number of shifts per day) - SE = scheduling efficiency (0 < SE <= 1) -> it decreases the number of available hours

(see back the difficulty of production management) > scheduling complexity > scheduling system is not capable to fully utilize machines with production orders, which finally corresponds to unefficient schedules > hence, in the model, time losses caused by unefficient schedules are estimated by the SE (correspondent to time losses due to scheduling efficiency) Available hours in the sense of the hours when we’re able to work, the factory is open; the system will work according to my strategic decision, so it’s given at the beginning of the plan It could happen that I will lose hours because my plan/scheduling is not all ok, is not the best, so the coefficient will decrease of the total amount of available hours

STEP 7 Calculate the number of machines of type i necessary to manufacture the production mix, given the yearly demand; it’s the ratio between the number of needed hours and the number of available hours 푁퐻푖 푁푀푖(푠) = 퐴퐻푖(푠)

STEP 8 The number that has been obtained must be rounded up or down depending on - Machine-type cost -> if it costs bililions, I should try to find an alternative

04. Design of Manufacturing Systems – Job Shop

- Possibility to outsource the production of some product-types - Possibility to use alternative routings for some product-types

Rounding down does not mean necessarily that the system is not able to reach the target production volume. The reason is basically related to the limits of the model with respect to the real operations: - coefficients are only estimates (based on past averages, experiences…, similar plants) - coefficients can be improved during operations (thanks, e.g., to better preventive maintenance policies) If the machine-type cost is high, it is wise to reduce (to reduce the financial needs / investment costs). One strategy is to reduce the workload required on the machine-type, by means of - outsourcing (i.e. moving workloads to suppliers) - planning alternative routings (i.e. moving workloads to other machine-types, less utilized or any how at least cost of the machine-type)

Evaluate the number of shifts/day, computing the yearly costs adopting 1, 2 or 3 shifts/day

푊퐹푖(푠) + 푂퐶푖(푠) + 푁푀푖(푠) ∗ 퐶퐴푖 ∗ 푚푖 + 퐹퐶푖(푠) ∗ 푓푖 - WFi(s) = yearly cost of direct and indirect labor - OCi(s) = yearly operating costs (e.g. energy costs) - NMi(s) = number of type-i machines - CAi = cost of a type-i machine - FCi(s) = installation costs of facilities - mi, fi = coefficients used to split costs on the machine lifetime or facility lifetime

(financia perspective) CAPEX versus OPEX: CAPEXs are splitted during the facility / machine life time > splitted cost can be then comparable (so, summed up) with costs representing OPEX. The mechanism to split is based on financial issues not detailed in this course.

(as a result) two possible choices when evaluating the alternatives of system design under the economical dimension (economic convenience): - (alt. 1) same shifts / day for all the departments vs. - (alt. 2) optimal shift for each department. Alt. 2 minimizes the cost function expressed in the above formula; but there are some costs still not considered in the formula: - cost of higher WIP & required space for stock holding, resulting from decoupling functionality of departments operating in different shifts - other extra-costs induced bythe different shift operations, both organizational extra-costs (e.g. workers with survellaince tasks through the plant, workers with material handling tasks …) and due to some shared plant structures whose operating costs are any how spent (e.g. heating central system switched on even if some departments are closed / not working during a shift)

12 EXAMPLE

Job X Job Y

04. Design of Manufacturing Systems – Job Shop

DATA X Y Yearly demand [units/year] 10000 50000 Lot size [unit/lot] 100 200 Human Coefficient 0.9 0.9 Type of machine Capacity Availability Cost (jobs that is possible % (x1.000 €) Yearly working days 220 to work at the same time) Hourly cost (first shift) 15 €/man hour X Y Hourly cost (second shift) 18 €/man hour Turning 1 1 100 50 Milling 1 1 98 150 Hourly cost (third shift) 20 €/man hour Drilling 1 1 95 100

1 operator for each machine; Amortization period of 5 years

05. Design of Manufacturing Systems – Manufacturing Cells

1 OUTLINE - General features - Examples - Strengths and weaknesses - Group technology – steps and methods - System design - Virtual cellular manufacturing

One problem of the job shop is that we have to move the products and materials through the different machines, so to reducing the wasting time of moving, we could put together the machines ➔ Grouping machines and production resources, in order to produce the certain product type/family; those groups are called cells. NB: it’s difficult to maintain a certain flexibility, which was the main benefit of the job shop

2 GENERAL FEATURES When cellular manufacturing is applied, parts are grouped into part families and machines into cells.

The machines are grouped on the basis of the processing requirements of the part families (different technological processes / machines in the same cell). Planning a manufacturing cells is easier than a job shop (ex: Toyota production system used at the start the manufacturing cells)

Here we can see boxes/cells with different type of machines inside, and we can see that we have one cell for each different product flow (different arrow), so the products pass through the different dedicated cell; in manufacturing cells, the machines are grouped according to the production flow, production requirements, type of product…

(*) Product and part are terms used as synonymous during this course

Layout and organisation of resources in the plant • The production system results from grouping machines based on a basic association between a set of parts / products to be produced and a set of machines capable to support their production > ideally, parts / products are assigned to families such that all the parts / products in the families are processed on the same group of machines, and similarly machines are grouped into cells if they process the same set of parts / products. • This approach (cellular manufacturing) leads to obtain cells made of different machines, offering different technological capabilities in accordance to the processing requirements of the parts / products

05. Design of Manufacturing Systems – Manufacturing Cells

assigned to the cell. In other words, the process plan (i.e. processing requirements) – i.e. the operations and sequence of operations – of each product / part in the families associated to the cell finds the different technological processes directly comprised within the machine groups forming the cell. Overall, the manufacturing cell is a group of functionally dissimilar machines that are placed together and dedicated to the manufacture of a specific range of parts / products. • In other words, no inter-cell move is required by the products / parts. In this case, we can talk of a product layout, as expression of the fact that the grouping criterion enables to re-arrange the group of machines so that they are physically adjacent (within the cell) + they serve only products / parts comprised within the families associated to the cell.

We have the technologies needed to produce this specific product; each mechanical technology could be used for producing different type of shape, but in a manufacturing cell they work in only one way It was born in mechanical contest, now it is applied in ……. MIN 21:50

The production resources are grouped together around a single space, because in this way one operator can easily work using one machine and another one, with little movements.

Each product has its own routing within the cell (this is the case when no inter-cell move is required > case of complete cell independence).

We have a certain product that can be done with a certain technology, but it can be done also by changing for example the dimensions -> product family; this product family can be derivate in different products For design the manufacturing cells, first I have to identify the different product families

Products, processes and product routings • This is the ideal case, occurring when the system design can achieve a complete separation of product routings amongst cells (i.e. part families visit machines pertaining only to the cell). • Overall, there is a positive effect on the shop floor: material flows are not intertwined as it is happening in the case of the job-shop.

05. Design of Manufacturing Systems – Manufacturing Cells

When cellular manufacturing is applied, it may lead to: - re-arrange existent equipment on the factory floor (i.e. machines, …); Manufacturing cells are normally designed reorganizing the system from a job shop, because is a more profitable method; it is a rearrangement of what is already existing. - operate with new equipment, often incorporating various forms of flexible automation (i.e. from machines, material handling equipment, …, to FMC/FMS).

In other words, a typical question related to system design is required – “which machines and their associated parts should be grouped together to form cells?” – before rearranging existent equipment on the factory floor or incorporating flexible automation.

2.1.1 Examples

2.1.1.1 Example 1 Different resources grouped together; it means that we are dealing with a manufacturing cell. It is used in mechanical, automotive industry. Since before the manufacturing cells exists, they use a method, grouping machine together and connecting them with automatic conveyor, robot, system who were trying to move easily the artifact from one machine to another: it is called “flexible

manufacturing system”

Context of the case - Tube manufacturer -> products for automotive applications - Technological processes available in the plant are used to carry out finishing operations of raw tubes supplied by the market; basically, we have cold processes (i.e. operations at room temperature) - Finishing operations consist of: cutting-off / cutting-to-length, bending, end forming, including chamfering and deburring, branching, welding …. ; therefore, the plant is offering a mix of technological capabilities to carry out finishing operations both as manufacturing operations (in order to achieve given shapes with given tolerances) and assembly operations

Plant re-layout, resulting after the application of cellular manufacturing - Root cause stimulating the need for plant re-layout > tubes are made of different types of materials > aluminium, plastic and steel > different hardness as characteristics of different materials (e.g. hard- and soft- tubes) > different processing requirements; - Originally the configuration of the system was a job shop, hence a system made of machines, with no rigid interconnection (material handling flexibility as in the job-shop) and grouped according to the same technological process; in reality, even if the technological processes were the same, there were different capabilities in terms, e.g., of installed electric power (different kWs) > different machines could process materials at different hardness > basically the material flows of different products / parts were then directed to specific machines (depending on their processing requirements and specific limits of the machines); - Suggestion: to take advantage by re-arranging the machines according to cellular manufacturing, resulting in three independent cells, grouping together machines according to the type of material as criterion >

05. Design of Manufacturing Systems – Manufacturing Cells

overall: no inter-cell move, cell independence + linear material flows (in/out of the cell) + closeness / adjacency of machines “within” the cell > potentials for time saving in material handling for parts / products assigned to the cell (based on a proper re-layout within the cell > this is required to decide how the different machines are installed in the space dedicated to each single cell)

2.1.1.2 Example 2 During the 70’s the production system started to be more automatic; it was flexible by the way of doing

Context of the case • Metal-cutting processes are used as technological processes while, as system, it is a FMS (Flexible Manufacturing System) for turned parts • Generally speaking, turning can be done manually, using lathes as machine tools (which requires continuous supervision by the operator) or automated lathes (which does not); today, the most common type of such automation is computer numerical control, known as CNC (CNC is also commonly used with many other types of machining besides turning > to control the motions of work-pieces, tools and other auxiliary functions). • This FMS includes 9 machines, the majority is CNC machines + some automated machines for specific operations required by the products manufactured in the system, e.g. a gear shaping partly numerically controlled. • Besides, robots are used for handling the work-pieces within each workstation, to and from the transport system (robotics). In regard to the transport system, four conveyor tracks can be seen in the figure. • Pallets are used for carrying manufactured parts + two central conveyor tracks are used as inner loop for recirculating pallets + two outer conveyor tracks have gates to the inner loop + the outer tracks provide the function of buffer storage > the left-hand track provides pallet storage and buffers in front of the machine + the right-hand track provides space to load/unload pallets carrying work-pieces to be manufactured / after their manufacturing; the conveyor tracks are made of different segments (along the loops) computer-controlled carry-and-free, e.g. in order to enable stopping in front of the required workstations; last but not least, manned operations is required at load/unload stations.

Prerequisite to build the FMS (before designing automation) • Parts were grouped into part families in order to identify common processing requirements > resulting in subsequent grouping of machines, according to the processing requirements > in this case, type of material + shape as criteria for part grouping > two types of shapes, disk-shaped and shaft work-piece, can be seen on the conveyor + work-pieces may be of steel, cast iron, aluminum. • In particular, shapes are a relevant characteristic in this specific case: parts are robot loaded into the machines (hence, from/to the buffer storage in front of the workstation to/from the working position of the machine tools); proper constraints (shape related) within the machine tools should be considered > even if there is an important level of flexibility in such machines (thanks to CNC and robot automation), some physical limits are still constraining handling & processing parts/products within the families identified so far

05. Design of Manufacturing Systems – Manufacturing Cells

2.1.1.3 Example 3 Context of the case • Similar reasoning in relationship to the Flexible Manufacturing Cell (FMC) herein schemed out • Main differences are related to the layout -> in regard to the transport system only one inner loop + a cart riding on a track above floor level + no robot is installed (> another system is used to load / unload the work-piece from / to machine tools to / from the cart (i.e. work-pieces carried by

pallets)) + overall, the system has a reduced size (FMC small versions of FMS)

Prerequisite to build the FMS (before designing automation) • Each part of the part families that can be manufactured in this FMC will be transferred to the machine tools/workcentres, thus visiting only those required by its processing requirements + the cart is the carrier used to transfer the pallets / work-pieces to the required machines/workcentres • To prepare this design automation, a pre-requisite was again grouping parts into families, and subsequently associating to groups of machines, according to processing requirements

2.1.1.4 Some other examples - https://www.youtube.com/watch?v=E54HAZWQpys - https://www.youtube.com/watch?v=c50lAIfzsk

3 STRENGTHS - Rationalization of material flows - Setup time reduction, reduction of wasted time; job shop are wasting some time, we are now dealing with cells, we reduce the “wasted time, working process, lead time”; I reduce the setup time because, in a cell the machine is used making the same type of action, we don’t have to make a setup every time we are loading a specific product, we have dedicated resources - Production management is easier

Overall (compared to the job-shop): - WIP reduction - Lead time reduction (also considering variability) - More reliable estimates of delivery lead times

Manufacturing cells provide different advantages with respect to the job-shop. - Rationalization of material flows -> when no inter-cell move is required (> case of complete cell independence), all material flows stay “within” the cell (> material flows are less intertwined than in the case of the job-shop) + all the machines to be visited are “within” the cell > expected time saving in material handling for parts / products assigned to the cell (> machines are closer, distances are lower than in the case of the job-shop - where the machines to be visited are located in different functional departments -, material handling time is reduced > more productivity of material handling -> more movements are possible at the same cost / number of resources). - Set-up time reduction > set-up times are reduced by using part-family tooling / fixturing > indeed, part families often imply set-up sharing potential > i.e. a machine may hold all the cutting tools necessary to make all parts in a family (i.e. similar materials + similar processing requirements in terms of technological parameters, as feed, speed, etc. for parts within a family > similar tools mounted on the machine > often, common tools b/w the different parts of the same family > often, no tool changeover is required b/w

05. Design of Manufacturing Systems – Manufacturing Cells

parts of the same family) + parts with similar shapes may fit in a generic fixture, with only individual parts inserts needed for minor adjustment (in order to fit to the specific part shape / dimension). Overall, the similarities of parts (shape, material, etc. …) within a family imply a favorable condition for setup time reduction by means of part-family tooling / fixturing.

As a consequence… - Batch size / lot size reduction > possible thanks to the set-up time reduction > subsequently (lot-sizing policy, economic perspective) economic order quantity would be reduced + (production logistics perspective) even if with minor batch sizes, proper machine utilization can be guaranteed w/o relevant set-up time loss (i.e. even if with more set-ups due to minor batch sizes, reduced set-up time loss on the machine) > less time loss for setup means then more production capacity that is effectively utilized for working / processing work-pieces.

For what concern production management (scheduling and control) of the manufacturing cell, this is easier (if compared to the job shop) - This happens for many reasons: o reduced size of the cell/production system o reduced set of parts produced within the cell, according to the families – cell association o reduced WIP that should be kept within the cell to guarantee the utilization of the production capacity (i.e. in other words, the target WIP (to be kept in the system) is not so high, and the machines are still sufficiently fed up with materials and properly utilized) (in other words, i)+ii) + iii) >>> the complexity of the combinatorial problem is reduced due to the limitations in the number of machines, number of product types/orders,...) - An additional advantage for production management is related to iv) closeness / adjacency of machines which is a very favourable condition for the adoption of simple techniques / practices of production control using visual management.

Overall, on the performances resulting as effect of the above mentioned strenghts: - For what concern WIP reduction, it is worth remarking that cellular manufacturing creates favourable conditions to this end -> WIP reduction is possible thanks to the small batch sizes + more linear / rational material flows -> in particular, with more linear / rational material flows, scheduling production orders would be less complex, and would lead on a short term to achieve a better control of variation of the workloads in different machines (less complexity for scheduling > better control) > hence WIP reduction as it is not needed a high protection to protect from variations. - Space requirement reduction > WIP reduction has a direct positive effect on the layout of the cell > lower space requirements to stock the WIP within the cell - A direct consequence of WIP reduction is also the reduction of manufacturing lead times LTs: due to the low number of production orders / batches present as WIP in the system, every time an order has an operations which requires to visit a machine, it meets a low number of orders / batches already waiting to be served by the machine, hence a limited queue in front of that machine. Low queuing times leads to low manufacturing LTs. - In regard to LT reduction it is possible to take advantage also of the closeness / adjacency of machines within the cell > as they are closer (than in the jobshop), an overlapping policy can be more easily applied > even if a production batch has not finished operations at a workstation, some workpieces (of the batch) can be moved w/o waiting to the next station (transfer batch size << production batch size); this is possible exactly because of the low distances / high material handling productivity; accordingly the transfer batch can already start new operations at next workstations w/o waiting finished operations of the remaining parts of the production batch at the previous workstation (> overlapping policy) - More reliable estimates of delivery lead times > if queuing times are low due to low WIP, variability of queuing times is also low > low variability of manufacturing LTs > more reliable estimates of delivery lead times > possibility to guarantee high delivery reliability (i.e. meeting the due dates) and better use of management system which assumes knowing the lead time to plan in respect to some dates (i.e. MRP)

05. Design of Manufacturing Systems – Manufacturing Cells

- Job enlargement + job enrichment for employees Normally in a job shop, the role of an operator is specific for one type of machine/technology; instead, a worker of a manufacturing cell has to know all the different type of machines which are in the specific cell -> the role is enlarging in the scope (enlargement), and also workers have more responsibilities (enrichment), they have to do more and more work, they are responsible of what they are producing normally workers are considered as higher experts, they know more activity, they run different machine, they self-control themselves ex: in Toyota production system, in the lean contest there is a specific role of workers - Team work within the cell The worker has to work with the different technologies not alone, but in a team; planning is an easier job - Unification of product and process responsibilities - More control on the quality characteristics of the products If in a certain moment there is a quality problem with a certain machine or material, in job shop it is difficult to find it out, in the manufacturing cell it should be automatically found by the specific operator The workers can do/have a larger control on machine

Initial Remark - Before introducing these further strengths, it is worth remarking that the traditional approach (and the majority of approaches) used to form & design cells consider cells in terms of their respective parts and machines, and regards the machines’ capacities as the factors that limit production (Russell et al. 1991). Besides, traditionally, methods only considered humans and their assignment to cells in terms of their labour capacity (Russell et al. 1991), or rate at which they can produce a part, while they do NOT in terms of the skills they possess, which is more a recent issue. But, as “real” problem (and lever to gain opportunities), the complete implementation of cellular manufacturing into an organization would require a major modification of the production system, resulting in very significant changes in worker roles (Hedge et al. 1994). - An important requirement for cellular manufacturing is in fact an increased level of technical skills and flexibility for workers, along with the ability to work in teams. Johnson and Manoochehri (1990) summarize the human resource requirements for success in cellular manufacturing: i) dedicated workers who have multiple skills (technical as well as communication and interpersonal skills); ii) who have the discipline to follow strict methods and procedures; iii) who are willing to make decisions and accept responsibility; and iii) who are committed to efficient and effective production.

Therefore, operators / workers assigned to a cell have relevant responsibilities - first of all, when the cell is manned (i.e. low level of automation), the workers have major responsibilities for setup, processing, material handling and also inspections (i.e. quality inspections). In particular, due to closeness / adjacency of machines within the cell, the workers have responsibilities to / can undertake a range of task along the process plans (operated through different machines within the cell) of parts within the family, e.g. processing tasks along the process plans > job enlargement; moreover, quality inspections are assigned to operators, which could lead to potentials of quality problem solving and any related decisions (even if it is worth remarking that product / process engineering is usually centralized and out of the cell, hence problem solving is not totally delegated) > job enrichment (involving the vertical integration of tasks and the integration of responsibility within the cell, thus assigning some autonomy to the cell itself) … Another e.g. of job enrichment is the assignment of control and production advancement tasks, with some responsibility (and autonomy) on disturbance handling of scheduled activities within the whole cell - it is worth underlining that more operators working within a cell are usually assigned to work regularly within the same cell > this is favourable for team working, with common responsibilities grounded on the job enlargement / job enrichment > leading the team to be responsible for the whole process plans of parts within the families associated to the cell, comprising quality characteristics

Comparison with the job-shops On the whole, comparing with the job-shop, the labour division in functional departments leads to limitation of workers’ responsibilities (and task specialization / skills) over the technological process provided in their functional departments > therefore, losing control / responsibilities along the process plans of products.

05. Design of Manufacturing Systems – Manufacturing Cells

Conversely, in cellular manufacturing, the families – cell association creates the conditions for the unification of product and process responsibilities > workers are responsible for the processes required by the parts of the families assigned to the cell. The unification of product-process responsibilities enhances potentials for quality control / improvements and delivery time control.

More details on quality issues For what concern specifically quality characteristics, control on quality characteristics of the products is enhanced as consequence of different (operational and organizational) conditions: i) small batch size, low manufacturing LTs, low time required for feedbacks to initiate problem solving > due to this quick feedback, there is more potential for transparency / visibility on the possible causes occurred along the production process; ii) combined with the team work, job enlargement + enrichment within the cell, and responsibilities of quality performance assigned to the team, there is a favourable context for quick discovery of problems as well as identification / collection of proposals for problem solving directly from workers within the cell.

4 WEAKNESSES - Difficulties with work load balancing between cells - Problems related to production mix variability - Difficulties with the application to the whole stages of the production chain - In some cases, necessity of more machines than in a job shop; in some case, I need dedicate machine, so more machines of a type have to be distributed in different manufacturing cells From a job shop to manufacturing cells, we have to add some machine to have a proper cell and working well, I need to know which machines of the job shop are not enough - Difficulties to manage technological operations outside the cells - Problems related to breakdowns, if a part of the cell has a problem, all the cell has a problem, it cannot work, it’s less reliable than the job shop

Designing a system with production cells, will introduce a certain rigidity, I’ll be less flexible than a Job Shop, because we are booking resource, spaces to be related to a product family, maybe for something that in the future will not be produced This type of system cannot change easily if the context will change (ex: the demand, the lead time of the suppliers), it will be difficult to group the machines in a different way, the system is rigid, less reliable, it is difficult to use it in the long-time; this happens especially in manufacturing cells which use automation.

Manufacturing cell means that we must have dedicated resources, so we must have some machines equal to each other distributed in the different cells

Cellular manufacturing is characterized by the following weaknesses: - Difficulties with work load balancing between cells (and between their machines) > a cell introduces some «rigidity» (it is less flexible …) with respect to the jobshop > this is a direct consequence of many matters: i) families – cell association; ii) the intentional design choice to avoid as much as possible inter- cell moves (i.e. the best choice should be no move, cell independence) iii) the autonomy of each cell (assigned with the integration of responsibility within the cell) > as a consequence of the «rigidity», it is possible that the work load generated by different families (in different cells) is not balanced across the cells (in some planning periods, some cells over loaded vs. some cells under loaded, and workloads cannot be transferred easily, or cannot be transferred at all, from one cell/its machines to the other cell/its machines, as alternative routing); within a job-shop, there is more «flexibility»: it is easy to assign a production lot / production batch to the underloaded machines, thanks to the routeing flexibility. - (Subsequently) Problems related to production mix variability > when production volumes between families are changing (as production mix is variable in different planning periods), workloads change leading to work load unbalance between cells (in some planning periods, some cells/their machines over loaded vs. some cells/their machines under loaded); within a job shop, changes in production volumes between parts/products are compensated and absorbed thanks to «flexibility».

05. Design of Manufacturing Systems – Manufacturing Cells

- Difficulties with the application to the whole stages of the production chain > the configuration of manufacturing cells is usually not applicable to the whole production chain, i.e. to all its stages; hence, the advantages obtained with the cells are limited and mitigated due to the influent characteristics of down and upward stages. - In some cases, necessity of more machines than in a job shop > (reasoning on a long term perspective) this is again due to the difficulties of work load balancing between cells/machines (cells/machines are over vs. under-loaded, in the long term) > it could happen that – ceteris paribus the total production volumes – the number of required machines is higher than in the case of the job-shop; in the job-shop, machines are loaded by all products, hence it happens that some overloading parts/products are compensated with other under-loading parts/products, and the number of machines might be lower exactly for this reason. - Difficulties to manage technological operations outside cells > even if the objective is to process all operations of parts of identified families within the associated cell, sometimes this is not possible > some cell dependence / inter-cell move is required or, at least, it is required to finish some operations out of the cells, either in a common resource in-house or in the premises of suppliers specialized in some technological processes. E.g. the heat treatments are typical technological processes / operations which, for the costs of the required machines / plants, cannot be duplicated in more cells; hence, it is preferable to keep them as common resources, either within only one selected cell or (often) outside all the cells > the disadvantage is that some material flows are now intertwined – due to families pertaining to different cells –, with the subsequent effect of reduced gains in terms of expected performance (e.g. queuing time / manufacturing LT variability in front of the machine outside cells could be higher, etc.). - Problems related to breakdowns > in a cell, the number of machines of the same type is lower than in the case of the job shop (at worst case, it is one machine) + the cell is built based on similarities of parts within families, hence an high share of parts may require to visit the few machines of the same type, requiring their capacity > when a breakdown fails, the impact is high, at worst stopping the cell, at best resulting in high capacity reduction impacting on high share of parts processed by the cell.

5 GROUP TECHNOLOGY We can define a cell with some steps, there is the list; this way of doing has been codified, step by step improvement, in group technology NB: the most important are the last two steps

STEPS - Data collection regarding the production mix and technological routings - Classification of products - Standardization of products - Standardization of technological routings - Identification of product families - Identification of machine groups forming the cells

Group Technology (GT) is an approach to manufacturing and engineering management that helps managing diversity by capitalizing on underlying similarities of parts/products and required activities/operations. - In general, by grouping items/parts which share common traits/similarities, GT facilitates the rationalization of activities/operations in a wide variety of functional areas, including purchasing, design, and manufacturing. - Concerning manufacturing, cellular manufacturing, discussed so far, is an application of GT: thanks to GT, manufacturing cells are created and operated > rationalization is achieved at shop floor level.

When GT is applied as to form manufacturing cells, the following steps are expected: 1) First step (data collection) aims at collecting data in regard to the product types, already manufactured and expected in the future, estimating the required production volumes (yearly demand) for each product type + defining their technological routings. 2) During the second step (codification and classification of products), all product types / part types should be assigned a part code (remark not to say but have in mind: in case PCA analysis is used); afterwards,

05. Design of Manufacturing Systems – Manufacturing Cells

they should be classified according to their characteristics, i.e. those relevant for further steps of GT application > characteristics such as, e.g., shapes, dimensions, materials, required tolerances (remark not to say but have in mind: both in case of eye-balling and PCA analysis is used) (we have already seen in some examples that these characteristics may motivate / lead to manufacturing cell formation). 3) Third step (rationalization and standardization of products) deals with an in-depth analysis of product / part types aimed at avoiding the product variety which is not necessary. Indeed, product variety may be induced by many reasons, such as: i) the introduction of new products in the product portfolio, ii) the existent product modifications and improvements, iii) the customization requests from clients. If we avoid product features / specs which are not really needed, product (re)design will have a great impact on the shop floor and on the definition of the proper configuration of the production system. 4) Fourth step (rationalization and standardization of technological routings of products) aims at reducing the variety of the technological routings of the product types (hence, not only product variety reduction as in the previous step). Ideally, in fact, if all product types had the same technological routings, production management could be simplified, material flows intertwining could be avoided, with subsequent advantages on better workload balancing in respect to the production capacity, achieving, overall, better performances. Two types of rationalization / standardization, reducing technological routings variety, may be achieved at two levels: i) (macro-level) operations sequences + ii) (micro-level) for each operation, standardization as much as possible of tools and fixtures needed to produce workpieces. A good practice to this end is simply to identify existing tools and standardize fixtures according to product shapes, during the product design and process planning/engineering steps. 5) Fifth step (identification of part families) aims at identifying the part families based on similarities of different parts / products in the product portfolio > parts / products are grouped into families based on similar characteristics: e.g. shapes, dimensions, materials, required tolerances, operations sequences … (see back, linking to step 2, required to prepare the needed information) 6) Sixth step (identification of machine groups forming the cells) consists of grouping machines according to the part families identified so far at previous step; this is done sequentially, that is: after the identification of part families, we identify the needed machines, according to their operations sequences; 7) Fifth + six steps simultaneously > identification of part families / machine grouping forming cells can be also achieved simultaneously > cell formation is concurrent to part family identification (see back, linking to step 4, which is related to the needed information, i.e. technological routings, with operations sequences and machines to be visited). Step 5 and 6 can be supported by different types of methods, presented in the remainder.

6 FIRST METHOD - IDENTIFICATION BASED ON THE CLASSIFICATION OF PRODUCTS It is based on the classification of products, on which we will create a manufacturing cell system, because a manufacturing cell is producing only a kind/type of product; there are different methods to classify the family: ARI 1.01 - Informal methods, when we are dealing with physical features o Based on geometrical features Probability if two products have the same shape, they could be produced by the same type of technology, they could belong to the same family ex: it’s valid in pharmaceutical, mechanical and textile contest o Based on technological features Different in their shape, but they can be produced in the same type of machine; starting from a raw material you have to apply the same technology, it is based on the technology himself

- Part coding analysis methods Codifying product has been introduced in the 60’s; all the components are linked to a number; the idea of codifying product has been invented to give a vocabulary system for the company: if the operator is able to read the code, he’s also able to create the product families There are different ways of Product coding: alphabetic, mono-code, numerical, … each company should have its own

05. Design of Manufacturing Systems – Manufacturing Cells

o Based on geometrical features o Based on technological features

Methods for Part-Family Identification (PFI), based on the classification of products (step 2 - 5) Classification of products consists, as said, of a classification based on the product / part characteristics, i.e. those relevant for further steps of GT application > characteristics such as, e.g., shapes, dimensions, materials, required tolerances... all in all geometrical / technological features. Two methods can then be considered for PFI, based on the classification of products: - Informal methods or visual methods or simply ‘‘eye-balling” methods rely on the visual identification of the correspondent part families (subsequently, the required machines, forming the cells, can be selected). o Plus: this method is trivial only when the number of parts / products, technological routings and machines is small (otherwise the identification task becomes impossible); the advantage of this method is that it is a quick method to implement, and requires no investment (it is only required the presence of an expert). o Minus: it is affected by subjectivity (i.e. different experts > possibly, different classifications of products > different PFI) and difficult repeatability (the same experts @ different times > possibly, different classifications of products > different PFI). - Part coding analysis (PCA) methods rely on a coding system. This is used o to assign (alpha-)numerical weights / digits to the part / product characteristics and, afterwards, o to identify families by using some familiarization scheme based on the numerical weights so assigned. More precisely PFI can be automatically implemented by means of an algorithm that o applies a filter to the whole parts’ set, basing on the part codes to look for similarities o forms part families using the filtered parts. PCA-based systems are traditionally product design oriented or shape-based, therefore they are ideal also for component (such as e.g. fixtures) variety reduction; other PCA-based systems may integrate different characteristics, spread from the geometric features (shapes and dimensions) to the technological features (material, processing requirements, tolerances …). o Plus: more formalized method, which leads to repeatability and objective outcomes. o Minus: the coding system that are normally available in a company are not necessarily ready for GT > e.g. they were built more for commercial purposes > this is the reason why step 2 of GT is required (prepare the coding system ..) > implementing a coding system may not be straightforward.

Method based on the analysis of the production flow are very different ARI 1.20/1.06

05. Design of Manufacturing Systems – Manufacturing Cells

INFORMAL METHODS

6.1.1 Based on geometrical features of products Different dimension means that we use the same resources, for example bigger the gear is, different is the machine we have to use (step 5 of GT) Part / product families are identified (PFI) based on geometrical features of products > i.e., shapes and dimensions of different products.

(Commenting the picture) > dimensions (@ similar shapes) of workpieces / products are initially different, when looking at the whole portfolio; dimensions are then used in order to lead to the identification of 3 part families, grouping the parts with similar dimensions > hence, there is a similarity for what concern the required workable volume > this is a useful information to select (at the next step of GT) proper machines.

This method is not only useful to identify part families but, as previously discussed, it helps also to standardize production components such as fixtures (i.e. similar shapes & dimensions > similar fixtures with minor adjustments in order to adapt to shapes & dimensions of different products).

6.1.2 Based on technological features of products, the type of machine the product need The products are very different, but they could be produced by the same technology

(step 5 of GT) Part / product families are identified (PFI) based on technological features of products > i.e., materials, processing requirements to obtain the required prod specs / features, tollerances of different products.

(Commenting the picture) > even if dimensions and shapes of workpieces / products are now quite different, there is another kind of similarity, concerning the processing requirements > turning operations are required by all workpieces > hence, similar processing requirements are used to identify part families > these processing requirements might then lead (at the next step of GT) to the selection of the same machine types.

PART CODING ANALYSIS (PCA) Part Coding can be used: - To help with blueprint design reuse - To form components families - To form the basis for cellular manufacturing design - To allocate new components to existing cells and easily plan process

05. Design of Manufacturing Systems – Manufacturing Cells

6.2.1 Part coding analysis (example 1) Part coding analysis (PCA) methods rely on a coding system. The part code results after assigning a set of numerical weights / digits correspondent to the different part / product characteristics established within the coding system (see the table for an overview of such characteristics). Indeed, each numerical weight will have a meaning according to the coding system so defined. E.g. part code 31000 means “metallic … plain” part while “000” could be used to expand the code with other information, in order to consider further characteristics.

(Commenting this example) > when classifying the parts, parts are recognized in terms of the following characteristics (geometric / technological features): i) material (metallic, non metallic, …); ii) shapes; iii) processing requirements (remark: some processing requirements are tacitly expressed beyond the shapes shown in the product drawings > e.g. “bent” requires “bending” processes; besides, some other processing requirements are expressed tacitly beyond the type of raw material > “cast, stamped, forged” requires to eliminate burrs, i.e. requires a “deburring” process.

Part Family Identification / PFI will be subsequent to having all the part codes available, then applying the relevant filters to identify the required similarities.

6.2.2 Part coding analysis (example 2) Part coding analysis (PCA) methods > this is the Opitz coding system > it comprises 9 digits representing a wide set of characteristics > it is based on geometrical and technological features, therefore different characteristics pertaining to these features.

(Commenting this example) >>> look at the 1st digit > “part class”, amongst “rotational parts” > there is clear specs in regard to the ratio of dimensions (length L / diameter D of the rotational shape) > well formalized method, helpful for the expert classifying based on the coding system.

Indeed, this coding system is even more formalized than the coding system of example 1, and more complete with more information based on the 9 digits. More in general, PCA, as said, guarantee more repeatable / objective PFI, thanks to their enhanced formalization.

NB: in the past there were specific operators dealing with the coding part, now there are specific machines, we are now dealing with codes

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6.2.3 Examples of part coding methods

6.2.3.1 Code hierarchical structure There is the main code, which refers to the family of product, which is derivate in different specific products

6.2.3.2 Polycode structure - Classification based on functions: o Morphological code o Technological code o Techno-morphological code - Classification based on code length: o Short codes (concise) o Long codes (code is extended with options and variants)

6.2.3.3 Hybrid structure

6.2.3.4 The Optiz Classification System Opitz code include a morphological (form) part and a technology part: - Original geometric code → 5 digit Digit/Position Type Feature/Group 1 Integer Part class (rotational/non-rotational) 2 Integer External shape 3 Integer Rotational surface machining 4 Integer Plane surface features and machining 5 Integer Auxiliary features (off-axis holes, gear teeth, etc) - Supplementary technology codes -> 4 more digits are added to the coding scheme, in order to increase the manufacturing information: o Dimensions (diameter or edge length) o Material type o Original shape of raw material o Accuracy (clearance tolerances or surface quality)

05. Design of Manufacturing Systems – Manufacturing Cells

Optiz is of Historical Interest as it was one of the first published classification and coding schemes for mechanical parts. Named after H. Optiz of the University of Aachen in Germany

Most of the time is something that it is present, it’s no done by an operator, but by the IT

6.2.3.5 Example

Rotational: L= 35 mm ; D= 50mm > L/D= 0,7 External shape: stepped to one end Internal shape: smooth Plane Surface: no surface machining Auxiliary Holes: multiple axial holes with pattern

7 SECOND METHOD - IDENTIFICATION BASED ON PRODUCTION FLOW ANALYSIS (PFA) There are different methods/models - Cluster analysis (we will use this method) o ROC (Rank Order Clustering) o Similarity coefficients - Graph partitioning - Mathematical programming - …

Methods for simultaneous Part-Family Identification and Machine Grouping (PFI/MG) (step 5 + 6 of GT, simultaneous) Part-family identification / machine grouping forming cells can be obtained simultaneously based on production- based methods (PFA). These methods are characterized by high potentials for applicability because the required

05. Design of Manufacturing Systems – Manufacturing Cells information is usually adopted at a company’s shop floor (i.e. material flows are known, because operations sequences and correspondent machines to be visited are in fact defined). Different methods are available amongst production-based methods > we focus on cluster analysis methods and, in particular, two well-known techniques within this type of methods.

PRODUCTION FLOW ANALYSIS (PFA)

Matrix of process/production flow that the product is following inside the production system: product A, B, C, D are produced in a specific or more than one machines -> It shows the product-machine relation; it has been created on an existing system, analysing the existing production flow

Now, we can put together the “X”, putting in different orders, we have reshaped the table in order to produce clusters, grouping the products which could be produce by the same machine, we are linking the products and machines which share the same production flow Using this table, we can have physical element for shaping the production system

Here we have implemented with the plan: - Letters are products - Numbers are machines

MIN 1.30

Those activities can be done in one single step or more than one; This way of doing can be used for a single part/product, or for the family of similar products, it depends on the different level of details (ex: in this example, product A can be a representative of a certain family of products)

05. Design of Manufacturing Systems – Manufacturing Cells

7.1.1 Rank Order Clustering It could give us an inspiration of how grouping different products, moving rows and columns to obtain the matrix; this algorithm has been codified during the 80’s - Step 1: read each row as a binary number (a list of 1 and 0) 1: the product is produced by this machine 0: the product doesn’t need this machine - Step 2: order rows according to descending binary number - Step 3: read each column as a binary number - Step 4: order columns according to descending binary numbers - Step 5: if on steps 2 and 4 no reordering happened go to step 6, otherwise go to step 1 We have to do those steps till all rows and column are ordered - Step 6: stop

Cluster analysis is composed of many diverse techniques for recognizing structures in complex data sets. Generally speaking, the main objective of this cell formation “tool” is to group either objects or entities or attributes into clusters such that individual elements within a cluster have a high degree of ‘‘natural” association among themselves and very little ‘‘natural association” between clusters.

Introdution to ROC - ROC is a procedure / algorithm that can be classified as an array-based clustering. In array-based clustering, the processing requirements of parts on machines can be represented by the machine/part matrix formulation. The machine/part matrix has zero and one entries (aij) > A ‘1’ entry in row i and column j of the matrix indicates that part j has an operation on machine i, whereas a ‘0’ entry indicates that it does not. - The array-based clustering techniques try to allocate machines to groups and parts to associated families by appropriately rearranging the order of rows and columns of the matrix to find a block diagonal form of the aij = 1 entries in the machine-part matrix > (cells are identified along the block diagonal form). - Overall, ROC procedure/algorithm uses as input the machine/part matrix and it aims at rearranging the rows and columns after converting the aij = 1 / 0 entries to binary numbers.

ROC Procedure / algorithm - Step 1 > associate a binary number to each row of the matrix > remember that in mathematics and digital electronics, a binary number is a number expressed in the binary numeral system, or base-2 numeral system, which represents numeric values using two different symbols: typically 0 (zero) and 1 (one) > hence to express the binary number of each row you have to sum extended from j = 1 to j = J (j-th index of the columns) of [aij multiplied by 2 raised to the power J-j]; - Step 2 > order rows according to a descendent order of the binary numbers so calculated (descending from top to bottom-hand side of the matrix); - Step 3 > associate a binary number to each column of the matrix > hence to express the binary number of each column you have to sum extended from i = 1 to i = I (i-th index of the rows) of [aij multiplied by 2 raised to the power I-i] - Step 4 > order columns according to a descendent order of the binary numbers so calculated (descending from left to right-hand side of the matrix) - Step 5 > if on steps 2 and 4 no reordering happened go to step 6, otherwise go to step 1 - Step 6: stop

7.1.1.1 Example - The machine/part matrix formulation is a matrix where the rows represent the machine types (rows i) and the columns the product types (columns j). - The machine/part matrix formulation provides the information of which machines are utilized / required / visited by different types of products / parts (aij= 1 or 0 entries). - No additional information is available in regard to the operations sequences, workloads generated by different product types on different machine types.

05. Design of Manufacturing Systems – Manufacturing Cells

- Example of computation of binary number of row #1 (sum extended to columns) (step 1) (binary number) 1 x 27 + 1 x 26 + 0 x 25 + 0 x 24 + 1 x 23 + 0 x 22 + 0 x 21 + 0 x 20 = 200 Every row, line of the table, that before was represent as “x”, can be easily translate in 1, when the product is produced in a machine, 0 if the product is not produced in that machine. Product one: is produced in machine A, F.

- descending order of rows (step 2) - example of computation of binary numbers of column #2 (step 3) (binary number) 1 x 25 + 1 x 24 + 1 x 23 + 0 x 22 + 0 x 21 + 0 x 20 = 56 You have to reshape the table, starting from the highest number, we change the lines, to create groups.

- descending order of columns (step 4) - no further re-ordering can happen (step 5) > end the procedure (step 6)

The table is fully ordered in terms of columns and rows, so the algorithm stops.

From this table we can see that we can create a manufacturing cell with - the machines A and F for producing the parts 1, 2 and 5 - the machines C and E for producing the parts 3, 6 and 7 - the machines B and D for producing the parts 4 and 8 MIN 1.44 For the machine C we have to open a discussion, because it is useful, with the machine E, for the parts 3,6 and 7, but it is needed also for the part 2; at the same way, the machine E is needed for the part 4 - Inter-cell moves: we will move the part 2 and 4 in the second cell (with machines C and E) from their specific cell (respectively, first and third cells); I need to produce a certain type of product using a machine belonging to another cells - Duplication of machine: I can put one machine of type C dedicated to one cell, another machine of type C for the other cells; in this way I will buy two machines of the same type - Alternative routing: for example, C is a drilling machine, and the drilling action can be made also in another machine, for example machine A -> the product will so follow an alternative routing, because we are changing the machine - Buy operation from third parties: I need machine C twice, but I have small volume -> I will not manage the production internally, I will buy that activity from the supplier; this is a planning decision, we can make hypothesis

05. Design of Manufacturing Systems – Manufacturing Cells

I have to consider different costs to understand which of these methods is better; from this table, we don’t know the value of the machine C, if it costs billions or thousands of euros They are called “exceptional parts”, I have to take decision, interpret what the table is telling me

Final steps of cell formation (after ROC ended) - See the cell formed so far, identified along the block diagonal form - See the cell dependence > The result of cell formation (after ROC procedures is ended) is often a solution where some cell dependence / inter-cell move is required: it could result that some part / product types should be processed partly in a cell and partly in another cell, it is the case of product 2 and product 4 > these are the so called exceptional parts > this leads to some problem to be solved > remember the difficulties to manage technological operations outside cells (see back amongst the weaknesses) - Three options are then possible, in order to finalize the cell formation and solve the problem related to the exceptional parts: o to accept inter-cell moves / cell dependence (e.g. product 2 and 4 have to work out of the cell, on machines C and E pertaining to another cell); o to duplicate the machine types interested by the inter-cell moves, within the two respective cells (but cost of duplication should be evaluated in respect to the advantages that can be obtained with cell independence); o to generate alternative technological routings for the exceptional parts (to avoid operations out of the cell); o to buy (externalize) the production of exceptional parts > operations are carried on by sub- suppliers (i.e. limited to operations outside the cell > problem of operations outside the cell not solved or the entire technological routing of the product, depends on costs).

SIMILARITY COEFFICIENTS Another method in order to elaborate the final matrix for creating the manufacturing cells. - Step 1: compute the similarity coefficients, in terms of how they are produced; we will calculate row by row, we calculate machine per machine the similarity coefficient 풏풊풋 풏풊풋 풔풊풋 = 풎풂풙 ( ; ) 풏풊 풏풋 - Step 2: join the couple (i*, j*) with the highest similarity coefficient, thus forming the machine group k Different things are grouped according to how much they are similar; this is a statistic method - Step 3: remove rows and columns related to both i* and j* from the original similarity matrix and substitute them with the row and column of the machine group k; then, compute the similarity coefficient -> 풔rk = 풎풂풙(풔풓풊∗, 풔풓풋∗) - Step 4: go to step 2 (based on a criterion: single machine group, or predetermined number of machine groups)

Another technique of cluster analysis is based on the adoption of so called similarity coefficients > we now introduce Similarity coefficient (SC) based methods; these methods rely on the computation of similarity coefficients in conjunction with the use of some clustering algorithm / procedure, in order to finally form the manufacturing cells.

Introdution to SC based methods - SC based methods are hierarchical clustering methods. Hierarchical clustering for Cell Formation usually comprises two macro-stages. Initially, some form of similarity or dissimilarity between machines (or parts) is employed, in order to prepare the creation of machine cells (or part families); afterwards, machines (or parts) are aggregated into a few broad cells, by means of a clustering algorithm / procedure. - The input of the method is still constituted by the processing requirements of parts on machines, that can be represented by the machine/part matrix formulation (as happened in the case of ROC). The calculation of similarity coefficients is carried on in order to build a similarity matrix where the values of similarity coefficients b/w machine (part) pairs are collected > each element of the similarity matrix (sij) represents the sameness b/w two machines (parts) / machine groups. Afterwards, a clustering algorithm is used to process the values of similarity coefficients, leading to draw a diagram called tree, or

05. Design of Manufacturing Systems – Manufacturing Cells

dendrogram, among all pairs of machines (parts) / machine groups > this tree visualizes a hierarchy of similarities amongst all pairs of machines (parts) / machine groups, accordingly with the similarity coefficients. Once available the tree, the machine groups forming the cell can be identified considering existent constraints and objectives, e.g. a minimum threshold for the similarity coefficients could be fixed and machines are grouped into cells considering their similarity coefficients in the tree (i.e. higher than the threshold).

Clustering procedure / algorithm in SC based method - Step 1 > initially, calculate the similarity coefficients for all machine (part) pairs i, j within the machine/part matrix. Considering machine pairs, the similarity coefficient indicated in the highlight means: ni = number of product types / part types that require to visit the machine i; nj = number of product types / part types that require to visit the machine j; nij = number of product types / part types that requires to visit both the machine i and j (common part types); if sij is “1”, at least one machine in the machine pairs is visited by the same part types visiting the other (the other machine may be visited by more part types); - Step 2 > select the machine pair i*, j* with the highest similarity coefficient, thus joining them in machine group k (have in mind that this is the first trial of a cell, not final cell formed by the method); now, we have a new machine group with highest similarity. - Step 3 > replace (in the similarity matrix) rows and columns i* and j* with the row and column of the machine group k, representing the pair i*,j*; compute the similarity coefficient of this new machine group k with all remaining machines (or also machine groups formed previously by the algorithm); due to the max formula, this is equivalent to find the max of similarity coefficients b/w each machine in the new machine group k (i*, j*) and each remaining machine (machine group) r . - Step 4 > the algorithm continues until a stop condition has been reached, i.e. all machines are grouped into a single machine group (containing the whole set of machines), or predetermined number of machine groups has been obtained

7.2.1 Example

The machine A and C are similar only by the product 2, so A is not too similar to C A and F has been grouped because they are similar on 3 out of 3 products

Comment the example Remark: When machine groups are progressively formed, remember to replace machines with machine groups within this matrix. E.g. in this case, this is needed at the final step (before ending with one single group) mach group BD, mach group CE, mach group AF are present in the matrix > each group is treated like a machine > that is: the similarity matrix is calculated b/w AF (r) and BD and CE (i*, j*) >this similarity coefficient is needed in order to complete the dendrogram (srk = 0,33)

05. Design of Manufacturing Systems – Manufacturing Cells

The dendrogram is a tree used to show the hierarchy of similarities among all the couples of machines (machine groups).

8 ROUGH DESIGN OF A MANUFACTURING CELL After the identification of product families and machine groups, the cells design can be based on the same approach used for the job-shop: - calculate the number of machines/working station of type i necessary in the cell; - evaluate the number of shifts/days, computing the yearly costs adopting 1, 2 or 3 shifts/day. To understand the number of hours, I will try to study the “available hours” and the “needed hours”, it is the same formula/design method used in the Job shops.

Once Part-Family Identification and Machine Grouping (PFI/MG) (step 5 + 6 of GT, simultaneous) is achieved, no verification has been done respect to the capacity limits. - Cell formation has identified only the machine types to be grouped within a cell, not their number. - We are now ready - knowing from previous steps of GT the production mix, technological routings, part families and machines forming the cell - to calculate the number of machines for each machine type necessary for each cell - The economic convenience of operating in different shifts / day should be also considered (as in the case of the jobshop).

Grouping techniques only group machines (or Material flow between Raw Material work centres-WC) together At the next level of detail, it is necessary to look at the flow rates and directions between resources in order to establish the best relative positioning of the machines within the cell This can be done manually (by “common sense”) or using techniques such as “To/From” analysis”, that allows to position WCs trying to linearize flows ➔ First develop From/To Chart, then define WC layout

05. Design of Manufacturing Systems – Manufacturing Cells

IMPROVING LAYOUTS USING CELLS

Improved layout - cross- Current layout - workers in trained workers can assist small closed areas. each other.

U shaped cells: resources, workers, machines are closer to each other, it’s a useful way to supporting the workers inside the cells, and also to move the materials; it can easily manage the process. It is valid for both production and assembly, it has been originally codified for the wide application by Toyota, Japanese. U shaped the line is typical of the lean production.

Current layout - straight lines make it hard to balance Improved layout - in U shape, workers have better tasks because work may not be divided evenly access. Four cross-trained workers were reduced.

U-shaped line may reduce employee movement and space requirements while enhancing communication, reducing the number of workers, and facilitating inspection

This is the typical work of an industrial engineer: choose which type of layout the cells systems should have, how to dispose the different machines.

9 VIRTUAL CELLULAR MANUFACTURING - Virtual Manufacturing Cells (VMC) are an alternative to traditional manufacturing cells, with the purpose to be more responsive with production mix variability. - In Virtual Cellular Manufacturing the machines that belong to a cell are not physically located together, but are identified as a group only by the Production Planning and Control system.

In Virtual cellular manufacturing, grouping of resources (i.e. machines) is not reflected in the physical structure > no re-arrangement in terms of layout; grouping is reflected in the PP&C system, which then enables to associate part families to group of machines > it is clear that this association is not «rigid» and may change in different planning periods. More precisely: - Depending on the production mix at a given time horizon, machines across various functional departments may be identified to form logical (virtual) groups, instead of physically repositioning machines one adjacent to the other. In order to achieve virtualization, it is then relevant to design logically how activities can be organized / controlled by re-assigning part families to groups of machines during the normal planning & control cycle. - One specific weakness of traditional cellular manufacturing that is addressed by VMC is related to the problems related to production mix variability > when production volumes between families are changing (as production mix is variable in different planning periods), PP&C will aim at work load rebalance between virtual cells (hence, smoothing, in some planning periods, the differences b/w some cells/their machines over loaded vs. some cells/their machines under loaded); that is: within a job shop / functional layout, the PPC builds up different virtual cells, gaining the advantages expected by cellular manufacturing (except those related to closeness / adjacency of machines) without losing the plus of «flexibility» - typical of job-shops – which can be used to compensate and absorb the variations of production volumes in the production mix from time to time.

05. Design of Manufacturing Systems – Manufacturing Cells

Comment the figure: Given the jobshop as physical structure, with material flows intertwining, the PPC system identifies group (Part family identification / Machine grouping forming cells) for a given planning horizon, so creating – during this planning horizon – the virtual cells, with subsequent advantages due to cell autonomy and rationalization of material flows (intertwining). The fact that this grouping is virtual is a prerequisite for the possibility of (virtual) re-arrangement in the next planning periods (with production mix variations).

During the years, we are still having the evolution of digital/automatic technologies, and so also of the production ones; Today, a factory is still using the concept of job shop, but the modern factory today can benefits of digital technologies and automation in system, in supply chain… The market is asking for new solution, and the IT are the right technologies, which could give a good level of flexibility, in manufacturing, automation is able to provide some “flexible solutions”: automation was something rigid in the past, now it is more flexible. You can implement a virtual cellular manufacturing, instead of moving a machine, you can take an automatic solution which takes the material and move it from a machine to another one: it’s the automatic guided vehicles (AGV). Today we can use the same approach of cells in a virtual way: we don’t have to move physically the product; we can solve the problem of movement with automatic system. Behind, there is the manufacturing cells, but it changes the machine and how the material is moved.

10 QUESTIONS FOR REVISION The following questions are concerned with the main contents of this lesson. They should help you to revise for examinations: - What aspects of job-shop layouts and transfer line layouts does cellular manufacturing combine? - What are the objectives of product group formation and machine group formation? What are the general procedures to form these groups? - Be aware of the procedure of rank order clustering (ROC) - What are the characteristics that have to be considered in the design of manufacturing cells?

11 REFERENCES - Burbidge, J., Production Flow Analysis (any publication) - Garetti, M., Design of production systems, FrancoAngeli, Milano, 2015 - Garetti, M., Lezioni di progettazione degli impianti industriali. CUSL, 2010 - Reid, R. D.,Sanders, N. R., Operations Management. 2nd edition, Wiley, 2005 - Slack, N.; Chambers, S., Johnston, R., Operations Management. 4th edition, Pearson Education, 2003 - Suri, R., Quick Response Manufacturing: A Companywide Approach to Reducing Lead Times. Productivity Press, 1998

06. Design of Production Systems – Transfer Lines

1 CLASSIFICATION OF PRODUCTION SYSTEMS

2 OUTLINE - General features - Examples - Strengths and weaknesses - System design

3 GENERAL FEATURES Each transfer line (also known as Flow Line) consists of a series of machines where a single product type (or a limited number of product types within the same family) flows, resulting in a routing through the machines.

A single product, we have or a certain type of product or few products belonging to the same product family. There are three transfer lines. The machines are different from every type of products, processes and product routings.

PRODUCTS, PROCESSES AND PRODUCT ROUTINGS A transfer line consists of a (group) series of machines: parts / products (limited number of product types within the family) flow through this series of machines, from outside the system/line to the first machine, then to the second machine, and so forth until the last machine, after which they exit the system / line.

06. Design of Production Systems – Transfer Lines

(Routing through the machines) we can talk of a product layout, as expression of the fact that the the transfer line is constituted by a series of machines resembling the operations sequences required by the single type of product, or the limited variants of products within the product family -> grouping machines according to the processing requirements of a single product type (of few variants/few product types). The series of machines is physically adjacent (within the transfer line, integrated with the material handling system). Overall, all the machines are then visited sequentially by the work-pieces, processed by the transfer line according to the process plans of product type. Parts / products are moved as a single piece or in small transfer lots correspondent to the number of work-pieces fixed on fixtures / work-holding devices used in the line. To this end, the series of machines is integrated with a common material handling system which moves parts through the transfer line, e.g. a conveyor belt > the movements of product items / work-pieces are constrained by the rigid interconnection due to the material handling system, and they are intermittent and synchronous (in case of synchronous transfer line) or asynchronous (in case there is the presence of inter-operational buffers b/w one machine and the adjacent one along the series of machines).

3.1.1 Part transfer: - Palletized transfer line: it uses pallet fixtures to hold and move workpiece between stations (i.e. transfer lots); - Free transfer line: the part geometry allows transfer without pallet fixtures.

- Intermittent: when all the products on the transfer line move with the same rhythm - Buffer: the different stations of line are not moving at the same rhythm; we have buffers between one station and another

- The production flow is serial - The transfer line is usually a highly automated manufacturing system: we need high investments, and to justify these investments we need stable and high products demand, it should be constant for all the lines - The demand of products should be high and stable - The line must be balanced: to ensure low WIP and a better lead time, we need to balance the production, to assign the products to the line in the balance way, trying to work at the same rhythm, to avoid bottlenecks between two stations

Summarizing the presented cases, it is possible now to remark the main characteristics / conditions that motivate the investment in a transfer line: - Technological routing of the product -> serial production flow / product routing -> product type(s) (product family) has to visit sequentially the machines, i.e. according with the same operations sequence (at least skipping some machine because there is no need for operations at such machines); - High production volumes + stable volumes through time o the demand of the product type(s) (of the product family) should be high enough to justify the installation, and thus to utilize sufficiently the production capacity so installed; o since the line design is dedicated to one single product type / few product types (of the family) the investment should be also justified by a demand of product(s) which is stable enough along the facility life time (to achieve return on investment) > transfer machines or lines are designed for mass production of a single product types (or a family of similar product types) over a long exploitation time > so to achieve an economically-reasonable investment.

Given these characteristics / conditions, it is worth remarking the main characteristics targeted by transfer line design: - the system design adopts high automation, in order to support high volumes each year (i.e. high production rates) of few products > this is the typical solution for mass manufacturing, with few product types in the portfolio (i.e. rigid automation, not flexible) > automated flow line; this type of automation is made possible thanks to the the characteristics of the line as: i) sequential interconnection of machines / workstation & serial production flow (see above); ii) limited number of operations along the line, defined once at design stage > overall, as transfer lines represent “high automation” they have large investment costs (sometimes hundreds of millions of euros) > so demand should be high and stable;

06. Design of Production Systems – Transfer Lines

- the system design places great emphasis on the efficiency/productivity (i.e. limiting time losses) and economy of scale (i.e. low unit production cost achieved with high volumes) in order to remain competitive (instead of flexibility, see the discussion already done for the job-shop), e.g. not many set-ups are scheduled, relating to the few product types in the product family > overall, low machine efficiency reduction due to total set-up times > better efficiency, better productivity, better achievement of economies of scale. In these lines, an item passes sequentially through all stations at a constant cadence. In order to achieve adequate performances of system design, the line should be balanced, that is: operations should be allocated / distributed properly to different workstations / machines along the line so to balance the workloads amongst them.

3.1.2 Transfer Lines

2. Transfer line with circular transfer (rotary table)

We can have specific machines, called specific (single purpose) machines or flexible work centres MANCA 6_00-8

3.1.3 Example 1 https://www.youtube.com/watch?v=rgbwkSLsaY4 Context of the case - Production of tube bed frames - 6 operations in the process plan of this product type + 1 load/unload > (tube loading) + cutting + welding + punching + end forming + bending + (final) punching + (tube unloading)

Description of the line - Automated transfer lines made of a series of 4 machines - The 6 operations are allocated to a series of machines along the transfer line: the parts (raw tube) enters from outside the system/line to the first machine (loading); the first machine is a cutting unit + welding seam (after cutting); then, the second machine is visited, where there is a punching unit + end forming unit; third machine is a bending unit; fourth machine

is a (final) punching unit; eventually, the product exits the system/line - Characteristic of the transfer lines, there is a synchronous part transfer > parts are transported b/w machines / workstations simultaneously (by the material handling system, which is activated intermittently in order to move the work-pieces every

regular / fixed time period, sync with the end of operations of all work-pieces at all machines). Hence no buffer, very compact transfer line + you will observe rigid automation / interconnection guaranteed by the material handling system.

06. Design of Production Systems – Transfer Lines

3.1.4 Example 2

Context of the case Automated transfer line (in the automotive sector), in this case this is an asynchronous transfer lines, in order to produce cylinder head of motor engines.

Description of the line - Transfer line is made of a high series of machines. - The work-piece (cylinder head) is moving through different workstations/machines each; each workstation is allocated a given set of operations out of the process plan. - The work-pieces are moved being fixed at a work-holding device (fixture), used to fix the work-piece both during the transfer b/w stations > a roller conveyor is the material handling system used to move the work-piece, by using a “power and free system” to achieve intermittent part transfer, and the processing at work-stations > again a linear flow (through the different machines, physically aligned according to the process plan). As can be seen from the layout, there is a linear material flow. - This is a case of N-stage buffered transfer line > see some segments of the conveyor along the line, just before or after each workstation/machine > in this case the transfer is intermittent + asynchronous b/w different workstations (systems with asynchronous part transfer, are referred to as ‘power-and-free systems’; in such lines each part moves independently of other parts) > the buffer is needed to enable independent movement > in fact, the material can be waiting in the buffer / segment before or after the machine / workstation b/w two movements (out old visited station – in new visited station) - Based on the design herein decided, here we have some flexibility (more than normal); this is due to the oversizing of machines (overcapacity) > we have more parallel machines than required > these machines can then be set-up with tools needed for different processing requirements (i.e. to produce different product types within the family) > this allows to produce at the same time different product types (of the same family) > this mix flexibility (leading to a mixed model production) has the cost of oversizing and it is not so usual; - Another interesting characteristic is the N-stage buffered configuration > the buffers, together with the parallel machines, are also a good issue for protecting respect to failures (if one machine goes down, the line – due to this oversizing – is not affected as a whole > at least there is some capacity reduction, but not whole capacity reduction).

06. Design of Production Systems – Transfer Lines

In this case we see we have some buffers between the working stations and oversizing of machines; we have also some parallelisation of machines; these characteristics enable the line to be more flexible and to avoid some problems along the lines; if a machine doesn’t work, the other machine can replace it in a small amount of time This kind of transfer line is called ?, because it moves the product in independent way

3.1.5 Example 3 Rotative transfer line, the products are on a table that rotate Context of the case - Automated transfer line, rotary transfer line. Description of the line - Transfer line is made of a low number / series of machines, installed along the rotary table: the rotary transfer machine is a cluster of 4 machines plus loading/unloading station, all connected by the rotary transport system. - The work-pieces are moved being fixed at a work-holding device, clamped to the rotary table (clamping is done at loading station). The work-pieces are then moved because the rotary table rotates every regular period (intermittent) of 90-degree angle (4 machines in front of the table), thus making the part transfer b/w stations. When the rotation ends up, the rotary table stops and starts the processing time at each machine. - As can be seen from the layout, there is a circular material flow / transfer, due to the physical configuration of the transfer line (hence a transfer is not only linear). - This type of system is adequate when high precision is required for work-piece processing, but it is limited in terms of space constraints to a low number of machines installed along the rotary table (geometric constraints > the rotary table is limited in terms of dimension, hence radius, hence space available adjacent to the rotary table, constrained and be used to install only a limited number of machines).

3.1.6 Example

U-Shaped Transfer Line; in this case we need half of the space: we have workers that can use more than one machine, they can shift easily from different machines, they are more flexible and the in and out part of the line is placed in the same zone, this simplify the management of the material coming in and out of the lines

Advantages: 1. … is more compact; its length is half the length of a straight line. 2. Communication among workers is increased because workers are clustered. 3. Compared to a straight line, flexibility in work assignments is increased because workers can handle more stations. 4. Materials entering point is the same as finished product leaving point, minimize material handling

3.1.7 Some examples - https://www.youtube.com/watch?v=Zx2GWXswP2I - https://www.youtube.com/watch?v=UO5dVrzwe0Y - https://www.youtube.com/watch?v=PxJqQnekJV4 - https://www.youtube.com/watch?v=uGyfm5PiwQM - https://www.youtube.com/watch?v=LxKrDX2b4ZU

06. Design of Production Systems – Transfer Lines

4 STRENGHTS Transfer lines are characterized by the following strengths. We can design a transfer line as a black box - Simple production management: we should focus on products batches o If we have different types of products in the line, we should define the batches (size and sequencing) o If we have a single type of product, we should define just the batch size - High machine utilization - Low space occupied We can address mass production which lead to big volumes and low production costs; to balance the transfer line, we have to allocate the operation in a balance way to the different machines in the line

First of all, for what concern production management of the transfer line, this is the easiest one (if compared to the other types, job-shop or cells). Management decisions are limited to two main problems: batch sizing + batch sequencing within a production campaign (i.e. batch sequencing is needed only in case of multi-model transfer line, which means producing batches of different product types within a given family during a production campaign); otherwise (the single- model case), the only decision is the number of production campaigns / batch sizes (hence, batch sizing) to be produced for the single product type (i.e. short digression to better understand this management decision > this is related to the typical set-up/cost of inventory holding costs optimization > when the number of production campaigns / batches is decided (e.g. by using Magee Boodman’s model), the batch size is also defined, being equal to Dj / No (i.e. demand of product j / number of production campaigns where, for each campaign, only a single product is produced)).

In other words, from the management perspective, the transfer line can be modelled easily as a black box, unique «equivalent» machine, as there is no real need for a more detailed modelling, because of many reasons (remark: not really true …. only for production management, this simplification is valid; for maintenance no… depends on degradation modelling): - the series of workstations / machines within the line are sequentially interconnected (by the material handling system), and the production flow is then serial (along the line) (> no particular decision for routing along the line); - WIP is limited by the number of workstations / machines along the line, at least in case of synchronous transfer line (> no real need for a specific control over this limited WIP within the line, enough to load according to a CONWIP); - only a single-model is produced at a given period of time by the transfer line; in fact, this happens also in case of multi-model production, because, in this case, the batch of a single product is produced at a given period of time (> when the product is decided, line balancing problem is solved, and there is no need for further decisions) -> overall, a good proxy is to model as single machine, at least for production management decisions.

Other strength is the high machine utilization: The high utilization of machines is enabled by the fact that we need small setup time, the products are the same or are product belonging to the same family, so the set up needed will be very low as the production mix is limited to products within the family and stable, it is possible to better control, thus optimizing, the workload balancing, hence achieving higher work load balance with respect to the job-shop (i.e. aiming at workload almost distributed in the same way along the line, even if not necessarily perfect work load balance) > well balanced and highly utilized; few products are included within a family (in case of multi-model) which means that, even if some set-up times are required, these should be limited, due to similarities within the family and limited number of products, hence limited changeover times > high efficiency > high utilization. Other strength is the low space requirements: a transfer line is normally a compact system, space is then limited, only due to the number of workstations / machines / material handling equipment along the line, at least in case of synchronous transfer line (+ some additional space for asynchronous).

06. Design of Production Systems – Transfer Lines

4.1.1 Subsequent performances Overall, subsequent performances, characteristics of transfer lines, are the followings - Low WIP - Low Lead time (also considering variability)

Low WIP > in fact, it is not needed to keep high WIP to achieve high utilization (in other words, to avoid underloading / underutilization of machines) > this is the case of the job-shop, where there is a clear complexity when managing material flows, intertwined and variable through time > hence, in this case it is proper to keep high WIP level to avoid time losses due to material starvation at some machines; here, in the transfer line, it is not the case, because of different reasons / characteristics of the transfer line environment: - the serial production flows (which makes this control much easier); - the (above mentioned) stability of the production mix/better work load balancing as a consequence and indeed this leads to define even a iii) the structural constraint that naturally limits the WIP along the line (see consideration on the space requirements / compactness of the line);

A direct consequence of Low WIP is also the Low manufacturing lead times LTs, thanks to the: - absence of queues (no buffer in case of asynchronous transfer line); - automated handling (> quick handling); - absence or at least limited size of transfer batches (i.e. parts / products are moved as a single piece or in very small transfer lots correspondent to the number of work-pieces – few - fixed on fixtures / work- holding devices used in the line > no time or at least limited time waiting for the processing of the pieces in the small transfer lot).

4.1.2 Other strengths - Low need for workforce, because this kind of lines are very automatized - Qualitative characteristics of products are stable, because the machines which act on the product are always the same, we don’t have variability of the different usage of machines, the pro

Other strength is the low need of workforce: the lines are very automatized, and the workforces are needed only for control, or for loading or unloading the lines, when it is not automatized - as said, the system design adopts high automation, in order to support high volumes each year (i.e. high production rates) of few products; - the tasks of operators / workers are then limited to control activities (control that the line is working / good functioning) and, when there is no specific automated system to this end, to load / unload activities (of materials to / from the line).

Other strength is the stability of quality characteristics of products: - no alternative technological routings is used > all the workpieces are processed by the same machines, thus avoiding differences due to the usage of different machines (differing for technological capabilities or precision level); - as the WIP is low, a quick discovery of deviations from quality standards and feedback – with few workpieces after deviations – is possible > subsequent capability to maintain the stability of quality characteristics (i.e. stop soon when there is a deviation).

5 WEAKNESSES - Low flexibility, different o The line is built for a dedicated type of product, we have to replant the line to change the product o If we want to add another type of the product, we need to change the routing of the machines, changing physically the line, spend a lot of time and money - High investment needed - Long time required to start new productions - High risk of obsolescence - Significant impact of failures

06. Design of Production Systems – Transfer Lines

The main weaknesses are enlisted in the remainder. First of all, a transfer line has a low flexibility > there are weaknesses in many flexibilty dimensions. - A transfer line is designed to produce a limited set of product types (within the family) or only one product type + a transfer line is designed to produce batches of the same product types at a given period of time (multi-model), otherwise set-up times could not be affordable; in some cases (rare), however, a mixed model is also possible because the transfer line has been designed to cope with such a mixed model production (see example 2); > any how limited mix flexibility; - the introduction of new product types is constrained > it is possible if the new product types share the same technological routing of existent product types within the family, for which the line is designed (and for which the interconnected handling has been defined); moreover, differently from the job-shop, each trial production / pre-series has high impact on the line, as the line has to be totally dedicated to trial production during a given time period, so stopped from the normal production; > limited product flexibility; - the introduction of new machines requires a reconfiguration and rebalancing of the whole system / line, which is NOT that easy, some constraints exist (e.g. rotary transfer); > limited expansion flexibility; - due to the high required investment, this type of system is usually built to work on more production shifts / high number of production shifts per week > hence, a small demand variation can be absorbed by using remaining shifts or overtime (i.e. times that are not normally planned), but these may be few options; higher demand variations – especially with dedicated / specialized machines - could be challenging, because of the needs to reconfigure / rebalance the line with the introduction of an additional machine (see back point iv) > sometimes this could be even not enough; furthermore, when the demand is decreasing, economic viability of the line design is soon affected > high impact on cost- effectiveness > the economy of scale is not exploited > the financial balance is soon worsening > > limited volume flexibility.

5.1.1 Other weaknesses: - High investment needed > due to the needs to introduce high automation for workstations and material handling system, in order to fully exploit potentials (i.e. for mass manufacturing) > high level of fixed costs; - Long time required to start new productions >>> new productions requires time for the changes required in machines, material handling system, automation system > time to reconfigure / rebalance the line; - High risk of obsolescence > the line is designed for / dedicated to a limited set of product types > facility lifetime is strictly related to products’ lifetime, that is: if products are their end of life, and they are not replaced by similar product types (within the family, using the same technological routing), the line becomes obsolete > overall, machines can be reused if they are general purpose, machining centers, while the line has become obsolete, and there is necessarily a transient period to reconfigure / rebalance the line for new productions (see back previous point); - Significant impact of failures > considering the series logic of equipment (machines / material handling system) within the line, the impact of a long machine downtime leads to line downtime; solutions used to mitigate the impacts of equipment downtime are the followings: o buffers b/w workstations, but – due to their (small size) – these are used to limit the effects of limited process variability (e.g. micro-stoppages, for ex. a tool breaking); o the installation of redundant machines > when there is a machine breakdown the other machines have still the capacity to produce the demanded production (but this has normally high costs, except in the case that the redundant workstation is featuring a low automation); o parallel machines whose nominal capacity is enough to produce the demanded production, while is partially enough in case of a machine breakdown (i.e. production capacity reduction). - This can be avoided trough the inserting of buffer or parallel machines, this allowed to absorb the event of failure of a single machine.

06. Design of Production Systems – Transfer Lines

6 INITIAL CONSIDERATIONS FOR DESIGN Lines are connected each other, also physically, they are dedicated production system, with conveyors/vehicles to create dedicated automated system: the term “transfer line” means automatic way, there is the movement from one machine to another one Let’s imagine to be a production manager, we have a demand of a product that is very high, to be fast, production manager can decide to invest in a dedicated system, transfer line - A remarkable similitude exits between fabrication lines and assembly ones (especially when automated lines are considered). - Most part of the techniques shown (sizing, balancing, buffering, etc..) can be adopted with few modifications in the two situations. - As assembly can require more the “human component” (i.e. in workstation), duration (time) variability of operations (tasks) and buffering issues will be tackled later on (in the assembly section). - In the fabrication line section, the sizing and the balancing issues will be focused on the deterministic case and without buffering (ref. paced). - Nonetheless, the concepts could be adopted for some cases of assembly lines.

With respect to previous industrial configurations (i.e. job-shop and cell) data are more deterministic Two different cases: - Mono-product (or single-model) - Multi-product (just some hints…) If you have a lot of products which need to be produced in short times, you can decide to invest in a production system with a dedicated transfer line

If we are designing a transfer line, we should decide the technology to use, so we have to: 1. define how the product should be produced, defining the operations and their sequence -> the production cycle; each working station can do one or more operation; from a list of operation, we should understand of how many stations our line will be made 2. get the cycle time 3. balance the line, deciding which single operation has to be done in one single stations-> made by the designer, also in assembly station

7 ROUGH DESIGN OF A TRANSFER LINE (SINGLE-MODEL) 5 main steps 1. Define the technological routing and operations of the product type 2. Identify all the machine types that are needed and balance the line on the given CT 3. Calculate the theoretical production capacity 4. Calculate the actual production capacity 5. Compare the actual production capacity and the demand. If necessary, modify the line and go back to step 2

7.1.1 Define the technological routing and operations of the product type Identification of the product type, to be manufactured, estimating the required production volumes (yearly demand) + defining its technological routing (comprising all information for the operations therein).

7.1.2 Identify all the machine types that are needed and balance the line on the given CT NB: A machine is a workstation The required machine types are identified based on the analysis of the technological routing / operations. The most relevant choice at this step is b/w specialized machines, dedicated to single or few operations (minus) but providing high speed performance (plus), versus machining centers / general purpose machines, that can process different / a wider set of operations (plus) at lower speed performance (minus) > (another plus) they can be used to configure the line, by replicating / using the same types of machining centers along the line (as a “module”, to which different operations are assigned) or, when the line is re-configured for new products (at the end of life of a product for which the line was previously configured), they can be re-used to enable the facility life extension

06. Design of Production Systems – Transfer Lines

(the line does not become obsolete because the demand of the product has ceased after some years … of course if there are no other factors, e.g. cost reduction of new technologies … which make the machining centers themselves obsolete). Line balancing problem (allocation of operations to work-stations / machines) is then resolved: Machining centers provides more degree of freedom for the allocation of operations, thanks to their flexibility, thus helping in line balancing; specialized machines are more constrained.

7.1.3 Calculate the theoretical production capacity 3600 푝 푇푃퐶 = [ ] CT = cycle time of the line [seconds/piece] 퐶푇 ℎ The maximum amount of working time of the line = maximum time to each type of machine to work on a single product As previously discussed, once it is known the allocation of operations to workstations, it is also known the CT = max working time (of the bottleneck machine) as well as the PC > herein defined here as theoretical value because no problem occurrence is considered in regard to the line functioning. Considering the typical unit of measurement of the CT in seconds / piece (i.e. very short time between exits of two successive work-pieces from the line), 3600 is used to convert to proper unit of measurement of PC / TPC (p/h).

7.1.4 Calculate the actual production capacity 퐴푃퐶 = 푇푃퐶 ∗ 퐴 ∗ (1 − 푆푅) [푝/ℎ] where - A = line availability (0 < A <= 1) we have to consider the availability of the entire line, of all the machines belonging to the line but also the whole system - SR = scrap rate (0 <= SR < 1)

Actual production capacity is a different value (lower than TPC) because of two main reasons: - scraps (defective products) - failures.

Therefore, the model includes: - 1-SR as the percentage share of good products, materials within the tolerance limits (respecting target quality limits) > TPC is then reduced simply considering the share of good products exiting the line during an hour, hence TPC x (1-SR); - failures happen leading to a machine downtime, which subsequently lead to a line downtime > in fact if a machine stops in a transfer line, due to the rigid interconnection (through integrated, common material handling system) each machine has to stop > this functional behavior is named, in system reliability analysis, as series logic > it can be demonstrated that, within the series logic, the Line Availability (time share of the system is UP respect to total time UP and DOWN) can be calculated as a multiplication of Availability of each equipment, i.e. Machine Availability x Material Handling System (remind that demonstration will be shown in a later section) > hence the APC is the TPC realized in output only during the time the Line is available / UP, hence APC = TPC x A (share of time the line is available) > SR and 1-A are considered as coefficients representing independent events and so they both reduce the TPC

7.1.5 Compare the actual production capacity and the demand. If necessary, if the capacity is lower than the demand, modify the line and go back to step 2 If APC < D (Demand of the product, i.e. demand rate, pieces / hours), re-design is needed, going back to step 2 - by including additional machines along the line which induce the need to resolve again the line balancing problem > this is then expected to lead – if well done - to reduce the maximum working time (of the bottleneck) > CT reduction > TPC enhancement > but there is a tradeoff > with additional machines, more machines in series logic > reduction of A; - by parallelization of more machines for the same operations (not detailed now) > potentials for CT reduction, TPC enhancement, A enhancement due to more reliable system structure; - changing the machine types (e.g. with different speed performance > different working times … etc.).

06. Design of Production Systems – Transfer Lines

Other decisions may consider, for example, the effect of enhancing preventive maintenance policies, aimed at increasing A beyond the inherent A (only with corrective maintenance policies), or of the repair policies, to achieve reduced downtimes > hence, again, enhancement of A.

MACHINE IDENTIFICATION AND LINE BALANCING Activities done by engineers who has to design the production equipment, you have to design the transfer line; NB: creating a transfer line for electric industry is different from one for the mechanical industry These activities tell us: 1. Define operations and their sequence; we should know the product and how it is produced 2. Get the required Cycle Time (CT), the time that each product spends in the transfer line 3. Compute the theoretical minimum number of workstations which allows us to have the “required cycle time” 4. Allocate the operations to the workstations; we balance the operations, each working station can do one or more operations 5. Balance the line and compute the efficiency of the solution; this activity is the same that the design does in the assembly system 6. Assignment of personnel (if any)

7.2.1 Define operations and their sequence - Breakdown and identification of fabrication cycle. The cycle is composed by elementary (basic) operations (tasks) - Definition of precedence diagram: it can be represented as a precedents table, Hoffmann’s matrix or the precedence diagram - Calculation of (deterministic) time for each operation

푇표푡푎푙 푤표푟푘 푐표푛푡푒푛푡 ∑ 푇푘 = 푆푢푚 표푓 표푝푒푟푎푡푖표푛 푡푖푚푒푠 = 푇1 + 푇2 + … + 푇푛 푘

Example: ∑ 푇푘 = 2.5푚푖푛푢푡푒푠

Some constraints (precedence) between operations exist, and can be expressed through graphs, charts, etc. Precedent diagram: diagram describing how all the single operations are happening, the order and the sequence of the operation; the definition of the precedent diagram is part of design, because it is a matter of technologies (it will be given to us)

Three issues arise: - Compatibility with precedences within the cycle - Finding technological similarities among operations, so to avoid duplication of particular technologies - (Static and dynamic balancing among the workload assigned to each station)

7.2.2 Get the required cycle time - The cycle time is the reciprocal of the production capacity (rate) required (units/h, i.e., the production volume to be processed in a given time, known from market demand (forecast)); usually expressed in seconds/unit (or minutes/unit) in such production systems

06. Design of Production Systems – Transfer Lines

- Cycle time is also the maximum time allowed at each workstation to complete its set of operations on a unit (if the required volume is to be achieved in the given time). If we have three operation allocated to the workplace, the sum of these three times should be lower than the cycle time

Opening time: 8 hours per day = 480 minutes per day Expected production capacity = 480 units per day CT = 480/480 = 1.0 minute/unit

7.2.2.1 Cycle time With 5 workstations, CT = 1.0 minute Cycle time of a system = longest processing time in a workstation.

We have five workstations, the total work content = 0,1 + 0,7 + 1 + 0,5 + 0,2 = 2,5 푚푖푛푢푡푒푠 Cycle time of this line is 1 minutes, which is the maximum content between the values of the single workstations, which is the bottlenecks

With 1 workstation, CT = 2.5 minutes. Cycle time of workstation = total processing time of tasks.

Now we are looking at the box of a single workstations

7.2.3 Minimum number of workstations Can CT = 1.0 minute? 푇표푡푎푙 푤표푟푘 푐표푛푡푒푛푡 ∑푘 푇푘 푁 = 푚푖푛 퐶푦푐푙푒 푡푖푚푒 퐶푇

Nmin = theoretical minimum (lower bound) number of stations required ∑ 푇 2.5 ex: 푁푚푖푛 = 푘 = = 2.5 푠푡푎푡푖표푛푠 ≈ 3 푠푡푎푡푖표푛푠 퐶푇 1.0

We allocate the cycle time of 1 minutes to the workload.

Workstation 1 Workstation 2 Workstation 3

7.2.4 Allocate the operations to workstations Allocation of operations to the workstations: using the precedence diagram and the associated operation times Tk, the operations are allocated to individual stations so that the sum of operations at each station does not exceed the work station time Ts (that is always ≤ CT). - Select the next operation to allocate: It is necessary to select only those operations that can be started according to the network precedence (pre-requisite operations must have been already completed (e.g. cannot tap hole until hole is drilled!). - Attempt to allocate the operation to the current station trying to use all of the available station time. When ∑ 푇푘 > 푇푠 it is not possible to allocate more operations to the current station and so a new station must be established.

7.2.5 Line balancing After allocating the operation, it can be required to balance the operation, there could be a bottleneck, something having more work than its possibility.

06. Design of Production Systems – Transfer Lines

7.2.5.1 Example of line balancing - Line Balancing is the process of assigning tasks to workstations in such a way that the workstations have approximately equal time requirements - Goal is to minimize idle time along the line, which leads to high utilization of equipment and labor - Perfect balance is often impossible to achieve The example is used in order to illustrate the line balancing problem: this is a typical decision problem at design stage of a manufacturing line, such as is the case for a transfer line. We take a transfer line, of 12 action, all with a duration of 1 minutes: there are three different ways to allocate the operations, it depends on the number of machines and the cycle time of each workstations The first two examples have the same number of workstations, but they have different cycle time - In the first module there is no balance between operations: a workstation has a cycle time of 4 minutes, then 2 minutes, then 3 minutes; the production capacity should PC = 15 pieces/hours - The second module has the same number of machines, but the content work of each of them is the same (3 seconds), so it’s balanced; in this case the PC = 20 pieces/hours - In the third case, we have reduced the number of machines, removing a workstation, and we group 4 by 4 the operations, balancing them, but the PC = 15 products/hours, inferior to the second case -> we have a machine less, but it decreases the production capacity -> tradeoff

7.2.5.2 Introduction to the example - The product flows from left to right, visiting the series of machines in a serial production flow + 12 operations (each lasting 1 minute) are required for producing the product manufactured in the line (i.e. from «A» to «L», according to a given operations sequence, first A, then B, … etc.). - Operations are then allocated to different work-stations / machines along the line (graphically represented by rectangle boxes) > different allocation alternatives are presented > see letters within the boxes to see how operations are allocated. - Overall, first two cases have the same number of work-stations / machines as a result (N=4), third case has a lower number (N=3) + other performance measures are CT (Cycle Time, minutes/workpiece) and PC (i.e. production capacity, or throughput, or production rate, used as similar terms, i.e. pieces/hour). - Cycle time is the time period elapsing b/w the exit time of the precedent work-piece and exit time of the successive work-piece from the line > this is constrained by the working time of the so called bottleneck machine -> (i.e. two meanings: longest processing time in the line-> correspondent to the most utilized). N = number of machines; CT = cycle time; PC = production capacity

7.2.5.2.1 Case 1 (not achieving a perfect line balancing > imperfect line balancing)

- Different working time requirements (workloads) are resulting as a consequence of the allocation so decided >>> the bottleneck machine is the machine allocated with higher working time (in this case the first machine). - All the parts are transferred synchronously every CT = max working time (working time of the bottleneck) > the maximum time which a product can spend at each station is a limit for the cycle time > CT cannot be lower than this value (otherwise, operations at some station could be not finished). - If we cumulate production during an hour, PC is simply subsequent to the CT > every 4’ a work-piece exits, at the end of the hours 15 pieces have been exiting / cumulated as output > in computational terms PC = 1/CT = 60 / 4 > in general lower CT, more frequency in exits, higher PC during a unit time (i.e. hours).

7.2.5.2.2 Case 2 (perfect line balancing > enhance production capacity)

06. Design of Production Systems – Transfer Lines

- All the parts are transferred synchronously every CT = working time of each machine > CT cannot be lower than this value (otherwise, operations at some station could be not finished). - If we cumulate production during an hour, PC is simply subsequent to the CT > every 3’ a work-piece exits, at the end of the hours 20 pieces have been exiting / cumulated as output > in computational terms PC = 1/CT = 60 / 3 > in general lower CT, more frequency in exits, higher PC during a unit time (i.e. hours).

7.2.5.2.3 Case 3 (perfect line balancing > reduce number of machines > reduce costs)

- Working time requirements (workloads) are resulting as a consequence of the allocation so decided >>> there is no bottleneck machine >>> all machines allocated with same working time (perfect line balancing). - All the parts are transferred synchronously every CT = working time of each machine > CT cannot be lower than this value (otherwise, operations at some station could be not finished). - If we cumulate production during an hour, PC is simply subsequent to the CT > every 4’ a work-piece exits, at the end of the hours 15 pieces have been exiting / cumulated as output > in computational terms PC = 1/CT = 60 / 4 > in this case, same PC as case 1, but lower number of machines, cost reduction.

Concluding remark: line balancing can be helpful to reduce costs of the line installation (i.e. number of machines installed along the line) or to enhance production capacity at fixed cost of the line installation.

7.2.5.3 Line balancing – Parallel stations

Total time: T = 15 minutes Cycle time (input data): CT = 4 minutes This diagram shows how the different operations could happen, it’s telling us the order and the sequence Without these two elements you can’t design a transfer line

To minimize the number of machines we can parallelize two machines - Our first station will be A+C, with the same time of B - We can group B, D and E and duplicate them, in a parallelized way -> the final ST is 4, because we have a ST of 8, but with two stations we doubled the output of the total station

7.2.5.4 Another example - Total time: T = 15 minutes - Cycle time (input data): CT = 4 minutes In this case the duration of B is 5, instead of 3, and the duration of D is 1 instead of 2 With the same configuration we can solve another issue

7.2.5.5 Objectives of line balancing and assigning tasks to workstations - Minimizing number of workstations - Minimizing cycle time - Maximizing efficiency - Minimizing production costs - Maximizing profits

06. Design of Production Systems – Transfer Lines

7.2.5.6 Compute the efficiency of the solution 푀푖푛 푛푢푚푏푒푟 표푓 푠푡푎푡푖표푛푠 푁푚푖푛 퐿푖푛푒 푒푓푓푖푐푖푒푛푐푦 퐸 = = 푇표푡푎푙 푤표푟푘 푐표푛푡푒푛푡 ∑ 푇 푇표푡푎푙 푡푖푚푒 푝푟표푣푖푑푒푑 ∗ 퐶 퐴푐푡푢푎푙 푛푢푚푏푒푟 표푓 푠푡푎푡푖표푛푠 푁 푘 푘 - N has to be greater than or equal to Nmin. It is not always possible to have a perfectly balanced solution in which all stations are highly utilised. - The suggested approach is perfectly valid for lines without statistical variability of operation time

7.2.6 Assignment of personnel Assignment of personnel (including more for absenteeism, physiological break, lunch time, need of all-around professionals, i.e., handymen), if any, but at least supervisors.

7.2.6.1 Example

퐶푦푐푙푒 푡푖푚푒 = 12 푚푖푛푢푡푒푠 푝푒푟 푢푛푖푡

푀푖푛푖푚푢푛 푛푢푚푏푒푟 표푓 푤표푟푘푠푡푎푡푖표푛푠 ∑푛 푇푖푚푒 푓표푟 푡푎푠푘 66 = 푖=1 푖 = = 5.5 퐶푦푐푙푒 푡푖푚푒 12 ≈ 6 푠푡푎푡푖표푛푠

퐸푓푓푖푐푖푒푛푐푦 = ∑ 푇푎푠푘 푡푖푚푒푠(퐴푐푡푢푎푙 푛푢푚푏푒푟 표푓 푤표푟푘푠푡푎푡푖표푛푠) ∗ (퐿푎푟푔푒푠푡 푐푦푐푙푒 푡푖푚푒∗) = 66 푚푖푛푢푡푒푠 = 91.7% [* among workstations] (6 푠푡푎푡푖표푛푠)∗(12 푚푖푛푢푡푒푠)

8 MODELS FOR LINE BALANCING During the years several design methods have been codified; some are very analytical, other are more heuristic: - Linear Programming (optimal) - Maximum fixed utilization rate (heuristic) o Simple method, without priority rules (i.e. the first available operation is assigned) o With local priority rules for assigning priorities, such as: ▪ MaxDur (longest processing time) ▪ MaxNFol (largest number of immediately following tasks/operations) o With global priority rules, such as: ▪ MaxFol (largest number of following tasks/operations) et similia ▪ Ranked Positional Weighting

Different approaches (using the same rule) can be adopted: - “Task-oriented” (when the remaining idle time is not sufficient to assign the i-th operation, a new workstation is opened), simpler, but less efficient; or - “Station-oriented” (when the remaining idle time is not sufficient to assign the i-th operation, before opening a new station, other available operations are taken into consideration to fill-up), less simple, but more efficient

06. Design of Production Systems – Transfer Lines

MODELS FOR LINE BALANCING – LINEAR PROGRAMMING

8.1.1 Main assumptions of the model: A. times to perform operation are deterministically known; allows to exclude the objectives to minimize the probability of no-completion B. requested production capacity is PC; allows to exclude the objective to minimize the CT (as it is given as a constraint based on PC). C. system composed of m parallelized assembly lines; D. absence of waste (defective products are reworked in a hospital station). The assumptions B, C and D allow to calculate the Cycle Time as: CT = m/PC. Once given the cycle time, we can limit the total idle time, by minimizing the number of stations (ALB 1st type ), which is the real decision to be taken through this model: it is possible to apply this method to find the minimum number of station, then it could be added to the solution the probability of no completion).

- i = index of task (i = 1, ..., N) - k = index of station (k = 1, ..., K) - CT = cycle time - ti = mean time of task I (is a deterministic value because of the assumption A) - cik = cost coefficient such that N·cik ≤ ci k+1 (k = 1, ..., (K-1)); it pushes to fill in first the previous station. It is a fictitious cost for pushing to utilize the previous station - IP = set of task pairs (u,v) with a precedence relationship (It is possible to use a matrix to enumerate the precedence relationships in a quick way → i.e. Hoffman Matrix) - ZD = set of task pairs that cannot be assigned to the same station - ZS = set of task pairs that must be assigned to the same station 1, if task i is assigned to the same station - 푥 = { 푖푘 0, otherwise

8.1.2 Objective function 푁 퐾

∑ ∑ 푐푖푘 ⋅ 푥푖푘 = 푚푖푛 푖=1 푘=1 Subject to 푁 7. ∑푖=1 푡푖 ∗ 푥푖푘 ≤ 퐶푇 k = 1, …, K 퐾 8. ∑푘=1 푥푖푘 = 1 i = 1, …, N ℎ 9. 푥푣ℎ ≤ ∑푗=1 푥푢푗 h = 1, …, K (u, v) Є IP 10. 푥푢푘 + 푥푣푘 ≤ 1 k = 1, …, K (u, v) є ZD 11. 푥푢푘 = 푥푣푘 k = 1, ..., K (u, v) є ZS

The model requires to predefine the number of stations K. Such value should be sufficiently high to enable a feasible solution; to minimize operators’ idle time, the model will force as much as possible operations in the first stations, leaving the others empty. The empty stations will be then eliminated. Thus, cost coefficients cik have precisely that role to force the utilization of the first stations before using the others. Indicating with K* the number of stations identified by the model, the resulting solution can be evaluated using the balance delay.

This objective function does not allow to allocate equally the total idle time between stations. It would be better to allocate equally the total idle time between stations: - to ensure more flexibility in production volumes; - to ensure greater job satisfaction; - to better accomodate the variability of the time to perform operations/tasks (it is better acceptable a growth of P* along the line, not a full utilization in first stations)

06. Design of Production Systems – Transfer Lines

8.1.2.1 Meaning of the constraints: 1. The first constraints’ class ensures that the sum of times to perform the tasks assigned to a station does not exceed the CT; 2. The second constraints’ class ensures that each operation is assigned just to one station; 3. The third constraints’ class ensures that each precedence relationship is respected; if the operation/task u directly precedes the operation/task v, then the index of the station where u is assigned has to be lower or equal than the index of the station where v is assigned. 4. 4. The fourth constraints’ class ensures that if u and v belong to ZD, they are not assigned to the same station (negative zoning) 5. 5. The fifth constraints’ class ensures that if u and v belong to ZS, they are assigned to the same station (positive zoning)

MODELS FOR LINE BALANCING – FIXED UTILIZATION ∑ 푡 The utilization rate of a workstation is defined as follows 푈푅 = 푖∈푆 푖 퐶푇 where: - ti = mean time of task i - S = set of tasks assigned to the operator - CT = cycle time For each operator, the following constraint has to be verified UR ≤ α, where α is the maximum value of the utilization rate (0 < α ≤ 1)

8.2.1 Steps 12. Draw the precedence graph (assembly graph) 13. Calculate the total tasks’ time T (sum of all tasks’ times) It can be defined as total work content or, equivalently, total time 14. Calculate the cycle time CT CT = available time / demand 푇 15. Calculate the minimum number of stations 퐾∗ = 퐶푇∗α 16. Assign tasks to stations, respecting the constraints (CT, precedence relationships, etc.); if there is more than one task available to be assigned, use a rule to priorities tasks

8.2.2 Basic Criteria Using the precedence diagram and the associated operation times Tk, the operations are allocated to individual stations so that the sum of operations times at each station does not exceed the work station time Ts. - Select the next operation to allocate. It is necessary to select only those operations that can be started according to the network precedence (prerequisite operations must have been completed, e.g. cannot tap hole until hole is drilled). - Attempt to allocate the operation to the current station to utilise all of the available time. When Tk equals Ts, it is not possible to allocate more operations to the current station and so the next station is selected.

8.2.3 Example Design the line considering: - α = 0,8 - Tc = 5' The time we have to consider is 4 (because alpha = 0,8, therefore 5*0,8 = 4).

06. Design of Production Systems – Transfer Lines

Balancing allows exploring several alternatives Operation #6 takes as long as cycle time (Tc), therefore we shall: - Looking again to the basic operations constituting operation #6 and determine whether operation #6 could be split into #6’ and #6’’ - Placing in parallel the workstation in which operation #6 is assigned; operation 4 and 6 have a total length of 8, therefore if we parallelize them, we will get a cycle time of 4 Operation code Processing time Begin 0 8.2.4 Fixed utilization with local rules (fake operation) More “complex” precedence diagram with cycle time expected: P1 15 Tc = 160 seconds/unit (α = 100%) P2 6 P3 30 P4 6 P5 30 P6 18 P7 6 MM1 3 MM2 15 MM3 15 MM4 15 MM5 15 MM6 6 MM7 12 MM8 3 MMF 0 8.2.4.1 Processing times MI 30 In case of a large number of operations it is crucial to set a rule for assigning ME 120 operations to workstations (so to set a sequence in which considering the available C1 106 operations) C2 6 C3 36 C4 6 I 6

FIXED UTILIZATION WITH LOCAL RULES 1. MaxDur, we select the operation with the longest processing time, and we see if we can perform it in the workstation we are considering. 2. MaxNFol, we rank the operations based on the number of operations following each of them and we allocate them based on this ranking. 3. Rank Positional Weighting, we define as priority index the 푃표푠푖푡푖표푛푎푙 푊푒푖푔ℎ푡 = 푡푖 + ∑ 푡푤 , which represents the length of the operation itself plus the length of the following operations.

8.3.1 MaxDur - The processing time of the i-th operation is considered as priority index. - Operations (those available) are ranked with descending order (thus setting as first the largest processing time ti). - Operations with larger processing time ti are thus assigned as soon as possible (when spare/idle time is more available …), thus having the ones with smaller processing time available for filling-up. - Sub-criterion (in case of equal score for first criterion): alphabetic order. - “Task-oriented” approach (when the remaining idle time is not sufficient to assign the i-th operation, a new workstation is set).

06. Design of Production Systems – Transfer Lines

WORKSTATION 1 WORKSTATION 2 WORKSTATION 3 WORKSTATION 4 OP DUR CUM OP DUR CUM OP DUR CUM OP DUR CUM BEGIN 0 0 MM5 15 15 MI 30 30 C3 36 36 P3 30 30 MM7 12 27 C1 106 136 C2 6 42

P5 30 60 MM6 6 33 C4 6 48 P6 18 78 MM8 3 36 P1 15 93 MMF 0 36 I 6 54 P2 6 99 ME 120 156 P4 6 105 MM3 15 120 P7 6 126 MM1 3 129 MM2 15 144 MM4 15 159

8.3.2 MaxNFol - The largest number of operations immediately following the i-th operation is considered as priority index (NFollowing). - Operations with larger number of following operations are thus assigned as soon as possible, thus increasing the number of alternatives. - Sub-criterion (in case of equal score for first criterion): - MaxDur or alphabetic order. - “Task-oriented” approach (when the remaining idle time is not sufficient to assign the i-th operation, a new workstation is set).

WORKSTATION 1 WORKSTATION 2 WORKSTATION 3 WORKSTATION 4 OP DUR CUM OP DUR CUM OP DUR CUM OP DUR CUM BEGIN 0 0 P4 6 6 MI 30 30 C3 36 36 MM1 3 3 MM3 15 21 C1 106 136 C2 6 42 P3 30 33 P7 6 27 C4 6 48 P5 30 63 MM6 6 33 I 6 54 MM5 15 78 MM8 3 36 P6 18 96 MMF 0 36 P1 15 111 ME 120 156 MM2 15 126 P2 6 132 MM4 15 147 MM7 12 159

8.3.3 Ranked Positional Weighting Prioritization: a task is prioritized by the cumulative assembly time associated with the task itself and its successors 푃푊(푖) = 푡푖 + ∑푤 푡푤 ; 푤 푖푛 푆(푖) where: S(i) successor tasks to task i

Unlike the method of the maximum value of utilization rate of operators imposed as a design criterion, this method allows to find a unique solution; anyway, since procedure is heuristic, this solution can not be the optimal one. To each generic operation/task i it is associated a priority (or positional weight, PW(i))). Such priority depends on the time required to perform the operation/task i and the sum of the times required to perform each task which requires, directly or indirectly, the previous execution of the task i. - ti = time required to execute the operation/task i - S(i) = set of operations/tasks which requires, directly or indirectly, the previous execution of the operation/task i.

06. Design of Production Systems – Transfer Lines

The basic logic of this heuristic methodology is to give higher priority to tasks followed by higher numbers of tasks. Such attribution allows to: - respect precedence constraints; - set “free” a greater number of branches of the assembly graph (i.e. executing first tasks which take precedence over the other activities, in the following stations it will be granted greater freedom in choosing between the remaining tasks).

8.3.4 Prioritization – steps 17. Task ordering o For all tasks i, compute the positional weight PW(i) PW(i) is the positional weight of the task i. It is calculated following the assembly graph. The times required to perform the operations/tasks and precedence constraints are taken from the assembly graph. o Rank tasks by non-increasing PW (thus ranking the PW(i) in non ascendant order.)

18. Task assignment For ranked tasks, assign task i to the first feasible station (obey the precedence relationships; do not exceed cycle time; obey other constraints) In the order defined in step 1, tasks are allocated to the first possible station, respecting: o the cycle time (or the maximum achievable saturation/utilization); o precedence constraints; o other constraints.

8.3.5 Example CT = 70 We have to choose first the operation with the higher PW: we can rank the PW and then we create stations, picking the first available operation, then you choose the higher PW if it is viable, then you continue like this

8.3.5.1 STEP 1 – Task ordering 푃푊(푎) = 푡푎 + ∑푤 푇푤 = 20 + 6 + 5 + 5 + 15 + 10 + 15 + 46 + 16 = 138 (..) Task a → rank 1

8.3.5.2 STEP 2 – Task assignment When at station 1 it is not assigned any task A the time remaining is the CT = 70 When at station 1 it is assigned task A the time remaining is the 70 – 20 (duration of the task a) = 50 …

The assignment ends when the CT is totally exploited (no more tasks can be assigned to the corresponding station). Note about utilization UR lower than 90%, max time allowed to make the work is 63 (so -7), so we have to move downward (to 2nd station), task g.

06. Design of Production Systems – Transfer Lines

Add another constraint: Opportunity or necessity to assign some operations to the same station, e.g. c and h have in common an expensive equipment (re-allocate moving operations from some stations… )

8.3.6 Assumptions - Pieces are manufactured in batches (batch A, batch B, batch C and so on); changing production from one batch to another requires a setup - Setup times do not depend on the production (batch) sequence

Modeling assumptions of system design - case of multi-model (more product types within a family) - The transfer line is used according to batch manufacturing approach: batch A of a product, then batch B of another product, etc. >>> to change from one batch to another, it is required a setup. - Set-up times are considered sequence independent: this could be either because in reality there is no sequence dependence (negligible), or it is the result of an optimization procedure that enabled to identify best batch sequencing (i.e. first batch A, then batch B, etc.) to reduce set-up times > in this last case, set-up times are given by assuming the scenario of optimal sequence.

9 ROUGH DESIGN OF A TRANSFER LINE (MULTI-MODEL) 1. Identify the production mix 2. Define the technological routing and operations of the product types (in the production mix) Identification of the product types, to be manufactured, estimating the required production volumes (yearly demand) + defining their technological routings (comprising all information for the operations therein).

3. Identify all the machine types that are needed and balance the line (for each product type) Same considerations as in the case of single-model >>> the line processes one product type at a time (multi- model), therefore the line balancing problem is solved for each single product (as before); the only difference is due to the fact that there is a constraint, that is: if N product types are considered in the production mix, N line balancing problem should be solved keeping fixed the machine types selected at each workstation of the transfer line > they are the same for all products.

4. Calculate the cycle time for each product type j 퐶푇푗 = 푚푎푥ℎ푇퐿푗ℎ [푠푒푐표푛푑푠/푝푖푒푐푒] where TLjh = unit working time of product type j at workstation h [seconds/piece] Calculate the cycle time as an outcome of the bottleneck machine identification; this is again based on the hypothesis that the line processes one product type at a time (multi-model) + the line balancing problem is solved for each single product >>> hence, bottleneck machine is fixed / identified when the product type is identified (> at a given workstation h).

5. Calculate the whole time to produce a batch of product type j 푇푗 ≅ 퐶푇푗 ∗ 퐻 + 퐶푇푗 ∗ (푄푗 − 1) + 푆푇푇푗 [푠푒푐표푛푑푠/푏푎푡푐ℎ] where - H = number of workstations in the line - Qj = batch quantity of product type j [pieces/batch] - STTj = setup time related to a batch of product type j [seconds/batch]

Approximating: 푇푗 ≅ 퐶푇푗 ∗ 푄푗 + 푆푇푇푗 [푠푒푐표푛푑푠/푏푎푡푐ℎ]

Calculation of the time required to manufacture a batch of the single product j, in case of synchronous part transfer. This results from summing up the times spent at three phases of the batch manufacturing process: o setup time, to prepare the line to produce product j (a first phase, seconds / batch) o time needed to complete the first work-piece of product j > there is in fact a load transient phase, due to the line throughput time of the first work-piece, b/w the load time and the exit time of the first work-piece in/out of the line; o time needed to complete the whole batch, except the first work-piece, of product j, paced by the bottleneck constraint/hence the CT (CT x (Qj – 1))

06. Design of Production Systems – Transfer Lines

Since CT is normally a low value, the approximated formula is properly applicable (and preferable for its simplicity).

6. Calculate the time needed for a set of batches (within a production campaign)

푇 = ∑ 푇푗 [푠푒푐표푛푑푠/푏푎푡푐ℎ푒푠] 푗=1,푁 where N = number of batches (one batch / product type j in the campaign) Calculation of the time needed to complete the set of batches (i.e. sequences of batches planned) in the production campaign (remind > the campaign might be expressed as a duration of time (a campaign of three weeks) or as a certain amount of production (a campaign of 22 batches)).

7. Calculate the average theoretical production capacity 푄푗 푇푃퐶 = 3600 ∗ ∑ [푝/ℎ] 푇 푗=1,푁 Similarly to the single-model case, calculation of the TPC. In this case, it is an average for the batch manufacturing during the production campaign of the line (>>> the Total quantities [pieces/set of batches] / total time for the campaign [seconds/set of batches] > [p/h], after conversion seconds to hours) > it is worth remarking that the average is weighted by the batch quantities of products j; as such, TPC depends on the production mix assumed within the production campaign (batch quantities Q j change > T and TPC change).

8. Calculate the actual production capacity 퐴푃퐶 = 푇푃퐶 ∗ 퐴 ∗ (1– 푆푅) [푝/ℎ] where o A = line availability (0 < A <= 1) o SR = scrap rate (0 <= SR < 1)

9. Compare the actual production capacity and the demand. If necessary, modify the line and go back to step 3.

10 QUESTIONS FOR REVISION The following questions are concerned with the main contents of this lesson. They should help you to revise for examinations: - For what reason do the work station times in flow lines have to be balanced? How is the balance achieved?

11 REFERENCES - Garetti, M., Design of production systems, FrancoAngeli, Milano, 2015 - Garetti, M., Lezioni di progettazione degli impianti industriali. CUSL, 2010 - Hitomi, K., Manufacturing Systems Engineering. 2nd edition, Taylor & Francis, 1996 - Reid, R. D.; Sanders, N. R., Operations Management. 2nd edition, Wiley, 2005 - Slack, N.; Chambers, S.; Johnston, R., Operations Management. 4th edition, Pearson Education, 2003

07. Design of assembly lines, cells and shops

1 CLASSIFICATION OF PRODUCTION SYSTEMS

- Fabrication has some material that are modified in order to obtain a component/product - In assembly there are products based on different components which have to be assembled

Most of the product around us are composed by many components ex: the chair is composed by different components, made with different technologies, and to obtain the chair we have to assemble

them

Assembly is a specific group of activities; most of them, nowadays, are done by humans/operators, we just need our hands; there are some machines, but less than in the fabrication system; in design assembly system, humans and its role are the most important activities

2 ASSEMBLY SYSTEMS – GENERAL FEATURES Assembly systems are systems which join together components (coming from systems which make the parts or subassembly them) in order to obtain finished products In assembly we have a lot of different solutions; in this way of seeing we can define the different level of variety (the number of types of products), volume (the number of products) -> there are different ways to assembly different components - Fixed position assembly -> archetype of assemble, with high variety of low volume of products, I have all the component near to me - Assembly shop and Assembly cell -> combination of fixed position and line; some activities are done as an assembly line, but the final assembly may be done in a fixed cell - Assembly line -> low variety but a high number of products; if the product change, also the line has to change dividing the line into stations: in each station each person is doing the same activity

In the Y axes we have the variety of product that has to be assembled; in the X axes the volume, the number of products that has to be assembled

This graph is telling us that there are different ways for planning the assemble of component

- fixed position: few products, or many different type - assembly line: the opposite, many products, high volumes and low variety - assembly shops: in the middle, an island with medium variety and medium volumes -> in the other spaces we have different ways of working; the two opposite are the most common and used one, but they can coexist

[Repetitiveness: how many times the same operations have to be executed]

07. Design of assembly lines, cells and shops ex: IKEA product ALRIK; we have the list of actions, that a normal person can do to assemble a chair. This is not so different from the assembly of a real production structure: in the companies there are different instructions/guideline made by some industrial engineers. In the instructions we see the final product, we have the information about the components needed and some information about what to do with them; there are 8 tasks, which, according to these instructions, should happens in a certain order -> we can construct the assembly graph (it is similar to the precedence diagram in the fabrication phase)

1-2-3-5 is a subassembly: it is one part of the components that have to be mounted in order to have the final product; assembly is usually the final assembly of the different sub assembled parts Activity 4 is not in the same subassembly as 1-2-3; so, it is a parallel operation that is happening in a parallel sub assembling (as activity 6)

In the reality, the document is the real work of the industrial engineer: for arriving to that document, you should know the products, process and what the operator can and cannot do, and they should find the solutions If we should prepare 50 chairs in a certain time, there are several solutions: - we can make a repartition of the work, we can build first 50 basements, then create 50 other pieces, and then mount all together - we can ask another person to help you -> make a division of work: given 50 people, each of them will be given the production of as single chair in the same way. The final result will be the same, what is different is the way of working.

If instead of building 50 chair, we should build 500 chairs: since the tasks are made in a specific order, we can put person in line, moving from one sub assembling to the next one. - If I do one chair for myself, I will do all the activities one time: fixed position; I have a working station and all the material needed are provided to me; obviously in the fixed position I can build everything for which I have the instructions. In the fixed position the person should have the proper competence, knowing everything about the chair because they have to do all the 8 operations. - If I have to build many chairs in one few time, you should have enough resources and person working in lines, dividing the work in small operation: assembly line is suitable for high volume production, in small time, and the variety (the type of product that should be made) is small. In the line 1 single operator is doing always the same operation. If I divide the operation, I do always the same activities, always mounting the same product, I should be train just if I mount a different product. - In the middle there are assembly shops, cells ex: IKEA product Alex; you have 24 operations: we have to builds the assemble graph, using the number of the reference in the catalogue

- After 9 we have the installation phase, then 10-11-12-13 - 14-15-16-17-18 should be done 5 times - then there is another subsystem 19-20-21-22-23 which should be done 4 times - the final assembly phase 18-23-13 NB: from this diagram we have no information about time and volume

The activities 14 are the same of 19, and so on, the only difference is the material that I need to take (in this case the shape of the box will change); this is quite common in assembly: I have different products with the same activities (ex: Toyota, in the same line they are making 5 different cars, this is possible because they have standardized the activities)

07. Design of assembly lines, cells and shops

Assembly systems are systems which join together components (coming from systems making the parts production or subassemblies) in order to obtain finished products. Manual assembly systems are composed of several stations in which one or more workers executes assembly activities. Stations are linked through a handling system (or transfer system).

Main resource: in manual assembly system the main resource is the workforce. - Advantage of depending on operators’ activities: this kind of systems can be properly defined flexible; it is a matter of necessary skills for making a range of operations -> versatility of the workers -> resources embracing a variety of skills, ability to handle multiple assignments/different operations - Disadvantage of depending on operators’ activities: variability of the manual assembly time, which determines challenges in the balancing and sequencing problem

Configuration: Fixed position assembly: the product does not move while being assembled, the required components are brought to the working station. All the assembly activities are executed in only one workstation. For this reason this solution is typically applied to heavy and bulky products (difficult to handle), e.g. machine tools, ships, airplanes.

Critical point: material handling systems are different and for different reasons -> should be taken carefully into account when designing an assembly system: 10. Material handling systems for material feeding: moving parts/components to be supplied; note the challenge: trend to have more and more part numbers for producing diversity of product variants in a product family -> trend to variety 11. Material handling systems for moving the assembly (product) on progress: again, there is some effect of variety but more on the line balancing and sequencing problem

Short intro of other configurations - Assembly shop: the product has to be moved through the different manual assembly workstations. Indeed, there is no rigid transport system, every product could have its specific flow through the workstations. The transfer could be manual or using AGV. The workstations are assigned a subset of all the operations of the assembly process. - Assembly line: the workers are stationary in the workstations and a transfer system moves the semi- finished assembly through the workstations where the parts / components are added in sequence until the final assembly is realized. The workstations are assigned a subset of all the operations of the assembly process. The transfer can be: o synchronous (absence of buffers between workstations), o asynchronous (buffers between workstations) or o continuous (operators move together with the assembly and at the same time they work on it or, similarly, the assembly is moving along the station and the operators are concurrently carrying out the assigned operations).

Some definitions applied to assembly, in order to classify the different configurations: - Variety: Variety of the assemblies (product types, variants within families) and, as induced effects, of assembly operations executed inside the work-stations of assembly systems. - Repetitiveness: Repetitiveness of the assembly operations executed by / tasks assigned to the operators inside the work-stations of the assembly systems (as opposite to the variety). - Flexibility: the ability to change or react with little penalty in time, effort, cost or performance (e.g. quality)» -> the ability of the assembly system to adapt, with low costs and times and penalties, to changes in the external or external context; Cost, times… etc. are both due to the assembly process as well as to the material feeding. - Volume: the ability of the assembly system to assemble a given range of volumes of assemblies (as opposite to flexibility …)

07. Design of assembly lines, cells and shops

Clearly in this scheme the fixed position assembly is located in the upper corner, to the right; depending just on the workforce skills, this system can guarantee: - high flexibility (the ability to adapt is gained by training the operators which are -by definition- the most versatile existing resource) -> operators in this system are highly skilled / multiskilled; - high variety and low repetitiveness -> substantially, the operator has to execute all the assembly activities required by the product; or at least a big portion of activities along the assembly process; - low volume as the high variety (low repetitiveness) of the executed activities brings to lower efficiencies for different reasons.

OTHER GENERAL FEATURES - Technology o Components assembly to make groups, sub-groups and finished products. o Operation can be reversible (or irreversible, e.g., welding) o Free technology route, with degrees of freedom o Low relevance of process technology parameters o Process flow is synthetic - Management o Relevance of management parameters (WIP, synchronization, lead time, delay, ...) - Cost structure o Low relevance of fixed assets, depending on utilization and customization of machinery o A lot of manual operations cause relevance of workforce utilization (focus on MANUAL)

Assembly system is composed by: - Workstations - Handling systems (belt, roller, and overhead conveyors, AGVs, forklift trucks, etc.) for parts (components) and WIPs (assemblies and subassemblies)

Assembly tasks do not usually require specific tools Need of correctly “feeding” the workstations - Small buffers in each workstations (for small and cheap pieces) - Use of overhead conveyors to bring (often large and heavy) components to workstations synchronously with respect to the main assembly (WIP) - Use of assembly kit: set of assembly and components (and specific tools)

CLASSIFICATION Three independent axes for classification: - Layout configuration - Production mix management - Task organization - Reciprocal movement of assembly, operator & components

2.2.1 Classification according to the layout configuration ex: assembly shop -> a helicopter is made of three big pieces mounted together. In the building in which the helicopter is made, the work starts from the body of the helicopter, and then there are 8 stations in which it is moved manually through wheels. In many days the first group of persons is mounting the interiors of the helicopter, in a certain order. Then the helicopter is moved to an assembly station in which another group of persons mounts other component, (engine and so on). So, the helicopter is moved in some days from one way to another. This way of organizing is not a line, since it is not moved in second or minutes, it is a combination of a line and a fixed position: it is called assembly shop ex: electronic industry is a mix of transfer line, in which I’m control board, and mounting lines, which are mounting the equipment: they are using the assembly shop or island assembly

07. Design of assembly lines, cells and shops

2.2.2 Classification according to the production mix management

An assembly is a group of person, resources and stations that I will use to run an assembly activity - in the first assembly system I’m always doing the same activities on the same product -> single model - in the second model we have different products in different orders -> multi model there are some setups, since I’m making 4 triangles and then 6 circles, and so on - in the third model, since the activities are the same but done on different components, I can have a different product in every line, if I can manage the different models -> mixed model ex: multi model, like in our example of Alex per Ikea: activities from 14 to 18 and from 19 to 23 are the same; if one guy is here, it can decide to take five of these activities (14 to 18) to be assembled, and then move to the other 5, or I can divide the activities batches by batches, doing 25 times the first 5 and 25 times the other five

NB: the different categories are combined: we can have assembly line working in mixed model, or we can have fixed position working in a mixed assembly system, or fixed position used for single model, or an assembly line that is managing the single model, and so on

Single-model system (ref. line) establish one assembly line for each product - Suitable for high volumes and stability of product demand - PROS: Low management issues - CONS: Low flexibility

Batch production: more products are assembled on the same system (ref. line) - Setup time are relevant (to substitute the components to be assembled) - Cycle time (CT) and number of workstations depend on the product to be assembled Need of good balancing and scheduling of all the products to be assembled on the same line (trade-off) High inventory of finished product (demand is not precisely satisfied)

With respect to a single-model line, more products are assembled in the same line - With respect to multi-model, the production batch size is equal to one (thus need for dramatically reducing setup time) - They are implemented with continuous and unpaced (often asynchronous) lines - PROS: Opportunity to follow the demand - CONS: o Need (compulsory) to reduce setup time o Need to properly schedule the products to be assembled o Difficult to manage component flows o Difficult to manage parallel workstations

2.2.3 Classification according to reciprocal movements Relationship between the components and the resources (human, machines, workstations) - Operator-Assembly o Operator → Assembly someone has to bring to the operator the materials Quite common in fixed position, the operator has its own workbench -> unpaced o Assembly → Operator the assembly is moving, and the operator is coming (ex: Ferrari) This is done in assembly line but also in fixed position -> paced continuous line - Assembly-Components o Assembly → Components the main components are fixed, and all the final assembly is moved in o Components → Assembly the main assembling is fixed, and all the component are moved in [“→” = towards]

07. Design of assembly lines, cells and shops

To design an assembly system, we need to know assembly diagram, volume to be produced and time needed Assembly cycle is the sequence of operations needed for assembly: it can be represented in a table with data related to any single operation In this table we don’t have just one time, we have also the average time and the standard deviation; we should know the expected time for each operation, and we need also the standard deviation, because the principal resource in the assembly line is humans, we know that all of us will work according to the normal distribution, they are not executing all the activities in the same exact time, all the time

Flow and precedence's of an assembly cycle can be represented by a chart (assembly graph), see example: - Final component → the final assembly, final product of the assembly diagram (ex: the final chair) - Sub assembling → assembly in which I’m mounting component needed for the final assembly

ex: ALRIK from IKEA -> this document contains instructions, guide line, that also non expert can use in order to assembly the chair, the final product; even in real industrial structure there are this kind of document, in order to support the operator

We have - final product - some information about the different components we have - some information to know what to do and how to do

These numbered activities are assembly operations of assembly tasks; in this case we have 8 main operations; we're no more dealing with fabrication, so we don't have the sequence diagram; in this case we have the assembly graph/diagram

At the number 1 we have the first activity put on the instruction NB: this doesn't mean that it’s mandatory that we have to do this first, it is a decision of who wrote the document From 1 to 2 we have a sub assembly, and according to this instruction, we can do the third action only after we have done the first and second Activity 4 is not a sub assembly, because we are keeping another part Activity 5 5 is built on the fact we have done all the previous activities, concept of sequence Activity 6 works on another part Then, when 6 is done, we can take what we have done in 5 and 6 and put together, in order to do the final assembly, represented by activities 7 and then 8, arriving at the final product NB: for arriving at that document, the industrial engineer has to know the product, the production process, the different components…

Let’s think if instead of assembly just one chair we have to build some of them, in a certain time There are several solutions for doing these activities - partialisation of work, making more pieces able us to fast the work - choosing the right amount of human resources -> division of work, you can do them alone or you can assign one product to each different person ➔ the result will be the same, but is different the way of working

In the case we have a lot of products, we can call a single person for each product, but we can divide the work in small pieces in a way that the work should be given to another one; in this way, one person works on the same line of the other people, one next to each other When we produce a low number of product (low volume), we can do the work alone

07. Design of assembly lines, cells and shops

2.2.4 How can we collect time and standard deviation Average assembly time Mk for each operation k and associated standard deviation Sk can be defined using the following methods: 12. work sampling -> trying to collect data, ask to experts to make estimation 13. standard times -> in a scientific way, libraries to estimate time, codified and written by other people MTM method (motion time measurement) -> we have the map of the distance that we should do, toward a certain object in a certain way; it is a simulation model that can calculate the expected average time and the standard deviation of one single activities Normally, these methods calculate the duration of each assembly operation by composition of elementary operations, therefore, first the values mi and si of each elementary operation, belonging to operation k, are calculated, then the duration Mk of the resulting assembly operation and its standard deviation Sk are calculated 푠2 by composition, this way: 푀 = ∑ 푚 푠 = √∑ 푖 푘 푖∈푘 푖 푘 푖∈푘 푛 The above relationships are based on the assumption of statistical independence among the various elementary operations of which k is made.

As human, every time that we are making an activity twice, we are getting some benefits, since we are learning how to work In determining the assembly times of manual assembly, it must be considered the so called “learning curve” that affects the work time due to the operator’s learning effect. In fact, the assembly time for a given activity decreases with the number of repetitions of the activity itself, tending towards an asymptote after some time (normally the steady state time is less than half of the initial time)

METHODS TO CALCULATE ASSEMBLY TIMES

2.3.1 Work sampling It consists in the observation of specific assembly operations and in the calculation of the average duration and standard deviation (Mk, Sk) of each operation using the standard statistical approaches. The method requires to create a sample of each operation’s duration by registering the assembly time of the repetition of the same operation. To provide reliable data, it is required to have a meaningful sample size. A drawback of the method is that it requires the availability of a real assembly station to monitor and collect data.

The work sampling method can be outlined this way: - Step 1: Choose and identify the assembly operation to monitor - Step 2: Inform the operator of the work sampling study - Step 3: Divide operation in smaller components (max duration 5-30 secs each) - Step 4: Calculate the required number of repetitions (accuracy) - Step 5: Measure the elapsed time for each work component (precise timing) and store captured data - Step 6: Calculate the average assembly time and its standard deviation

2.3.2 Standard times Standard times are called the data on elementary assembly operations calculated with the work sampling method in a company (i.e. in real assembly conditions) and stored in the company data base. This way a database is made available with data related to “basic” assembly operations. Therefore, if real data of elementary operations have been correctly collected and transformed in standard times, the duration and standard deviation of a new assembly operation can be calculated by composition of the standard times of the available elementary operations data.

07. Design of assembly lines, cells and shops

2.3.3 MTM (Motion Time Measurement) method It is based on the assumption that, based on an archive of elementary operation data (where duration and standard deviation are assigned, based on custom parameters of the operations like the weight lifted or the angle of movement) it is possible to compose any complex operation and calculate its average duration and standard deviation. Nowadays the use of CAD computer programs makes this approach much easier and more precise than in the past. In fact, CAD-like computer programs allow to model any movement of the operator and his interaction with the equipment. After that, automatically, the computer program can generate the exact sequence of the various elementary operations and pick up corresponding data from MTM tables, thus calculating the final values of Mk and Sk.

MTM (Motion Time Measurement) is the most commonly method used - A database of elementary operations is used to calculate by operations composition the average time and the standard deviation - Based on basic (elementary) human movements - Method for calculating: o Tables of elementary human movement times under different circumstances are available o Times are expressed in “TMU”s – Time Measurement Units (1 TMU = 0.00001 hr = 0.036 secs) o Add the times of the different elementary movements necessary to compose the needed operation and convert to seconds or minutes Advantages: - Quicker and cheaper than time study (work sampling) - Reliable (based on large number of studies) - Planning and estimating new jobs - Useful for short runs - Rating already incorporated

2.3.3.1 Example of a MTM reach table Reach operation table: how to calculate the TMU of a reach activity Distance Hand in Time (TMUs) moved Motion Cases and descriptions (inches) A B C, D E A B =<0.75 2.0 2.0 2.0 2.0 1.6 1.6 1 2.5 2.5 3.6 2.4 2.3 2.3 A. Reach to object in fixed location, or to object in other hand 2 4.0 4.0 5.9 3.8 3.5 2.7 or on which other hand rests 3 5.3 5.3 7.3 5.3 4.5 etc B. Reach to single object in location which may vary slightly 4 6.1 6.4 8.4 6.8 4.9 from cycle to cycle 5 6.5 7.8 9.4 7.4 etc C. Reach to object jumbled with other objects in a group so 6 7.0 8.6 10.1 8.0 that search and select occur 7 7.4 9.3 10.8 etc D. Reach to a very small object or where accurate grasp is 8 7.9 10.1 11.5 required 9 8.3 10.8 etc E. Reach to indefinite location to get hand in position for 10 8.7 11.5 body balance or next motion or out of way. 12 9.6 etc Hand in Motion – replace above A & B times if the operators’ hand 14 10.5 is already in motion etc etc

07. Design of assembly lines, cells and shops

3 FIXED POSITION ASSEMBLY

GENERAL FEATURES In a fixed position assembly, the product is assembled in a single site, rather than being moved through a set of assembly stations. Materials (i.e. components), equipment, tools are brought to the site. I have each person in each workbench, and the single person will assemble the entire chair. Workbench are desks, in which I have all the elements to do my activities, it is a working area in which there is a person that is mounting and assembling the components. The industrial engineer should know the number of workbenches and which type of workbench are available

Usually it’s expensive in terms of space, and experienced person are needed, according to the type of technology - ex: expensive watches as Rolex are built in assembly system in fixed positions, since watches need experience person doing the different activities - production equipment (machine) are mounted in fixed position for logistic question because they are big and difficult to move

3.1.1 Description of this type of system Every workstation (i.e. the manual station) could be modeled as a unique block, physically correspondent to a single site (as space in the shop floor) for which: - the input are the various necessary components to be assembled (all those required by the BOM); - inside the system, such components are assembled together; all the tools and equipment required to assemble the components must be there (in the site); - the output is the unique finished product.

Every workstation is involved in the assembly of a different types of product (in the example 2 workstations assembly the product A, the other twos assembly the product B and the product C, respectively -> mix flexibility is reached thanks to the parallel stations prepared for different product types, i.e. equipped with proper materials/components, tools,… , and trained workers).

3.1.2 Characteristics of products typically assembled by this type of system Generally speaking, this kind of system is chosen to assemble: - Heavy and bulky machines (machine tools, turbines, aeroplanes) which require the assembly of big amounts of parts; this leads, at the end, to build an heavy and bulky product. - Such products are generally required in small quantities (aereoplanes, aero engines). Since these products are generally required in small quantities, the building of an assembly line dedicated – costing for its structure (i.e. capital expenditures e.g. for a fixed material handling system) – for them wouldn’t be economically justified and strategically justified (i.e. low volumes calls for flexible solutions -> flexibility). The big size (physical volume/dimension) and the heaviness (weight) of the machines justify the choice of this kind of system, since all the assembly operations are made in a single site, thus they do not require to move such a bulky product from the site (which would be of course a challenge).

- Simple products/objects required in medium quantities and requiring few parts to be assembled (small toys or subassemblies of more complex products). The limited range of necessary components doesn’t justify the splitting of the workload in more workstations, while the moderate volumes required doesn’t justify the building of an assembly line -> again, an economic convenience but also some practical matter in the work organization -> few tasks are assigned to the same operator in the case of fixed assembly system.

- Fragile products, difficult to handle because movements could create scraps (e.g. hi-fi system).

07. Design of assembly lines, cells and shops

3.1.3 System characteristics and criticalities: - All the components must flow to the single site – depending on the scheduled products (normally mixed models or multi models …); this creates a complex flow in managing the input of components to each site (i.e. complex logistics management in the factory to feed the components). - Work-force assignment: in a workstation, depending on the complexity of product, one or more operators could work; therefore, each operator executes the entire product assembly cycle or a significant part of it -> required multi-skilled workers; as the assembly process is divided in few operators, the cycle time is by definition long.

3.1.4 Physical structure and organization of the single site: - components are stocked around the site (challenge: need for room/space to place components); - assembly equipment and tools are placed around the working position where the product to be assembled is positioned (need for room/space to place …); - the product is placed in the central area of the workstation (working position). o in the case of heavy and bulky products, they are located on the ground / floor in a delimited zone; o conversely, small products are placed on a worktable / assembly work bench. - the operator works on the product while standing and moving in the surrounding area.

NOTE: the space required depends on the kind of product to be assembled, the number of parts to be assembled and their characteristics (amount and size), the number of tools/equipment …. It is important to design the workstation following the ergonomic principles. For instance: - locate materials and components in way that ease operator movements so to be efficient and to be safe; - provide the equipment onto adjustable bases to adapt their height to workers characteristics; - etc. … Whether standalone work benches or interlinked workstations in assembly lines, the structure is similar, but of course the space requirement are different (depending on the operations required in the workstation).

EXAMPLES

3.2.1 Case of small products repair shop (shop replaceable units of radars in jet fighters) 3.2.1.1 Introduction The bill of material (BOM) for maintaining the radars embedded in military airplanes is usually multi-level. The FRU (Field Replaceable Unit) are functional units that can be replaced by ground operators: when a FRU fails, ground operators substitute it with a “new” FRU he/she has available in the warehouse. The damaged FRU is hence sent to the Maintenance Center. “New” FRU means the FRU should be considered as it is brand-new (i.e. “as good as new” in reliability theory): it can be that a FRU has been already submitted to a previous revision/reparation, where components have been already replaced because broken or because they reached their end of life stage. It means FRU is not functioning, due to a failure; failure is generally defined as the situation when an entity (i.e. FRU or other entities in the BOM) can’t execute a required function (UNI EN 13306). A single FRU is made of many SRU (Shop Replaceable Unit), which in turn are made of several assembled electro- mechanical components. There are two ways to repair a FRU, either the damaged SRU is replaced with a “new” one, or some of the electro-mechanical components are directly replaced in the original SRU. 3.2.1.2 Comments on the fixed position assembly of this case - Both reparations (SRU replacement or component replacement) can only be executed by the specialized workers from the Maintenance Center. - The workers are working in a workbench on such small objects/products and fragile + note that the workers are multi-skilled and specialized. - Note the ergonomic solutions in the workbench …. (e.g pneumatic screwdriver).

07. Design of assembly lines, cells and shops

3.2.2 Case of (rather) small and fragile products - Hi-fi systems, high quality production (take care of non quality generation) + high level end item (in the market), moderate to low volumes; Linn Products developed the single-station build concept where one operator assembles, tests and packs the product; each operator works at a fully equipped position to which material for a day's build is delivered / fed by Automated Guided Vehicle(AGV); he then builds, packages, tests and signs the product ready for despatch to maximise performance and quality; - Whilst a typical hi-fi industry product may be manufactured in minutes as cycle times, assembly cycle times at Linn can be hours for the most sophisticated and innovative designs (which is aligned to the low volumes -> low requirements for the production capacity).

3.2.3 Case of heavy and bulky products - Aeroplanes: case of more operators working on the same workstation/fixed position (on the ground within the hangar) -> a relevant portion of the assembly process is assigned to each of them; most of them are working partly parallel in time (as it is possible, many of the respective operations are not constrained by precedence relationships); - Aero engines: it is clear that specialized workers are required, to which different assembly tasks are assigned; it is basically another solution where the site is built by handling the product thanks to an equipment fixed on the roof.

See these videos - https://vimeo.com/112937014 - https://www.youtube.com/watch?v=HB5BAfEH45Q - https://www.youtube.com/watch?v=NBCDgoabHF4 - https://www.youtube.com/watch?v=L27ZtsU0a40

STRENGTHS - High flexibility - Low investment - Job enlargement, enrichment and rotation for the employee

3.3.1 High flexibility - Mix flexibility: (short period) it is possible to assemble different types of product in the same time, meeting specific and periodically changing demand requirements (i.e. high variety in the same time, different variety at different times). This is due to the independence and the decoupling of the workstations (in a given period, if you need to assemble more products of type X, it will be sufficient to dedicate / prepare more workstations to that type of product) -> of course workers should be trained to change…. - Product flexibility: to introduce a new product, operators just need to be trained to acquire the new required skills for new types of product, while the physical structure can remain substantially the same (new product being close to characteristics of existent products -> normally few simple tools / equipment are required even with changed products -> it is quick to start with new production of new product types / prepare the workstation to this end). - Expansion flexibility: (long period) it is not difficult to add new workstations, thanks to their independence/decoupling, the only constraint is room/space.

3.3.2 Low investment It is, of course, due to the system simplicity -> the building of new workstations doesn’t require particular structures; of course, expansion flexibility may be possible (if there is room/space for this): - the investment value may be increasing if some necessary equipments are expensive; - in this case, it is advisable to buy a limited number of equipment and, through a correct scheduling, make them available to the different workstations whenever they are required (obviously, this solution would make the logistics management more complex and lead to some “interference time”)

07. Design of assembly lines, cells and shops

3.3.3 Job enlargement, enrichment and rotation for the employee - Every operator executes the entire product assembly process (case of simple products), or a significant part of it (case of bulky products). - The workload is not split between the various workstations (as in the case of the assembly line) and this means more gratification for the operator: o high number of different operations / tasks assigned to the station/operator -> low repetitiveness of tasks -> more gratification; o Job enlargement (more, different tasks along the assembly process), enrichment (other types tasks than only assembly, quality ctrl, test, repair, packaging, feeding), rotation (in case of heavy and bulky machines, forms of job rotation can be actuated within the groups of workers assigned to the station)

WEAKNESSES - Potentials for intertwining of material flows - High WIP - Large space requirement - Labour training might be difficult and time-consuming - High cost for workforce

3.4.1 Potentials for intertwining of material flows Every necessary material/component has to be brought to every workstation + every finished product has to be handled from every workstation. Such issues creates problems relating to internal, intertwined flows. The problem will be more relevant with the increase of workstations number. Conversely in assembly lines, the material flow is extremely rationale -> every single workstation along the line is fed with just its pertinent components; then the finished product is taken from just one specific point (the end point of the line), instead of every single workstation. For this reason, in fixed position assembly, a logistics management of flows is challenged by many issues, and inefficiencies are existent, due to such a complexity on the floor, having different I/O points, the site of the materials, possibly with different requirements, i.e. multi/mixed model assembly).

3.4.2 High WIP Cycle times are high at each workstation -> subsequently, one or more pallets of components (as input) are kept for a long time as WIP; besides, also the finished products (as output) are normally not delivered immediately after the end of the operations (still a WIP then) waiting for some time before the material handling (i.e. complexity in logistics) come to serve. Then, in buffers by the station, many components and finished products may be stocked. On the contrary, in assembly line there is a natural and continuous flow of semi-finished assembly and finished products, which leads to limited WIP along the line and finished products being regularly delivered out of the line to the further logistics activities …

3.4.3 Large space requirement Clearly it is linked to the reason above: there is a need for room to place components and finished products. Moreover, while an assembly line is a compact system, the fixed position assembly requires additional room between different workstations to allow a safe material handling.

3.4.4 Labor training might be difficult and time-consuming As a consequence of job enlargement, enrichment and rotation for the employees (as more different operations are required within a significant variety of products), they do need time to learn and be trained on how to execute their tasks.

3.4.5 High cost for workforce This is strictly related to the difficult and time consuming labor training (see the reason above). Workforce will be highly qualified, well trained.

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ROUGH DESIGN OF A FIXED POSITION ASSEMBLY Number of single sites /stations The number of stations Nj for the product j can be calculated as follows: 푁푗 = 푃퐶푗 ∗ 푇푗 where: - PCj = requested production capacity for product-type j [pieces/h] - Tj= time required in order to complete the assembly process on a piece of product-type j [h/piece] The number of fixed positions is based on the expected capacity and the delivery time I would achieve

The rough design of a fixed position assembly simply consists of determining the necessary number of single sites/manual stations. Such number – referring to a piece of product type j – has to be calculated starting from the knowledge of: - the average (total) time required in order to complete the assembly process on a piece of product type j; - the required production capacity for product type j. The value of the requested production capacity has to take into account the value of the waste which could be produced during the assembly process; generally the waste in manual assembly acquires the meaning of rework/repair, typically for products of high value. It means that PCj consists of the target demand and the losses of time (consider the scrap rate => rework rate due to quality control,..).

Observing the formula: - If Tj is very high, and PCj is low (case of airplane or in general heavy and bulky machines), Nj is low. - If Tj is low and PCj is medium (case of toys or in general simple/small products), Nj may increase but it is still low. Remember that PCj is generally NOT high because - otherwise – it wouldn’t be correct to build up a fixed position assembly: actually if the number of stations increases, for ex., the “intertwining of material flows issue” becomes excessively relevant, and in general, the strategy should look for other solutions (i.e. lines) more oriented to the efficiency (eventually with some flexibility).

4 ASSEMBLY SHOP

GENERAL FEATURES An assembly shop consists of a series of stations and each station (generally, more than one station) is assigned a phase of the assembly process of a product type. A mix of different product types can be produced within the assembly shop and its stations.

The presence of different product types – having a wide range of different assembly cycles/processes or different required volumes – makes the assembly shop a suitable alternative to the line solution (one or more lines). In particular, this requires a strong decoupling of the stations, so to enable managing this mix.

The assembly cycle/process is decomposed in a certain number of phases, each of such phases is assigned to a certain number of parallel stations, as in figure. Generally, each single station (to which a phase is assigned) is able to perform the entire phase. Stations belonging to consecutive phases are not connected by a rigid transfer system, but a flexible one. Then, there is not only a single flow for all products, but flows are interwoven (intertwined). Each station has an upstream (or input) buffer (where products are dropped, waiting to be assembled) and a downstream (or output) buffer (where the assembled products are dropped, waiting to be handled to the subsequent station); buffers decouple phases: if they are properly sized the system doesn’t depend on the handling system.

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HANDLING SYSTEM The handling system provides to stations also the needed components (inserted in suitable kits). The handling system can be manual, automated (AGV) or semi-automated. - AGV (automated) -> control of the travelling mission -> computer already knows where the vehicle has to go (and controls the execution of the move phase); besides, a supervisor is present as a computer that assigns the travelling missions to the AGVs (so scheduling the routing of workpieces through the plant); - Hand cart (semi-automated) -> the operators have to move pieces from stations to stations and have to make the L/U; at each station there are lights which help to understand the state of the stations; because of the closeness between stations, it is not so important to optimize travels, and we can rely on the operators flexibility to make the L/U of small sized materials, moved by an hand cart (some wastes in move can be experienced); the operator would know when to move when he sees the control lights at green state (to update the operator in regard to the actual dynamics); it is probably using a card system that can be directly placed in the hand cart (the card is saying what is the operations and type of stations) -> so he knows where to move

The handling system can be traditional (carts guided by operators) or automated (AGV). In case of AGV, there are many possible configurations, for instance: - “taxi”: the handling system transfers the product from one phase to the subsequent one: the product being assembled is handled by the AGV and it is dropped in the upstream buffer of a station, then the AGV moves away to perform another transfer. When the operator finishes to perform the assembly, he drops the product in the downstream buffer and he calls back the AGV (not necessarily the same AGV which dropped the product at his station). Meanwhile, another AGV has dropped another product in the upstream buffer of the station. For this kind of system, the presence of a control and transfer optimization system is really important: such system must minimize the number of transfers (w/o moving pieces, empty) and the handling distances. The taxi system can be used when durations of assembly activities -at least- last a few minutes (typically cycle time – so the time assigned to the station –should be at least 5-6 minutes). - “working table”: the AGV -instead of dropping products in buffers- are provided with adjustable working tables which allow operators to perform assembly activities while moving. This solution is recommended when the cycle time is short, since it is not convenient to drop a product at a station if it will have to leave the station after a very short time. Viceversa, if the time assigned to the station is high, this may require an oversizing of AGVs, so it would be not convenient.

4.2.1 Examples

Two cases of a car manufacturer and semiconductor manufacturer (comments on mid variety / mix & volume) The stations are equipped with automated machine (ex: in the case of the car manufacturing, there are robot making the welding operations … etc.)

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- AGV - Zone where the AGVs are charged their electric battery - Stations with I/O buffers, many paths to reach stations

Flexibility implemented in a specific solutions adopted -> conveyor with an inner loop and many loops leading to the stations - The central conveyor tracks are used as inner loop for recirculating pallets with the product under assembly; this serves as a buffer storage; - The outer conveyor tracks have gates to the inner loop + the outer tracks provide the function of move towards the station where the phases are assigned There could be manual or automated stations https://www.google.it/search?q=gripper&biw=1920&bih=971&source=lnms&tbm=isch&sa=X&ved=0ahUKEwjfm5byu7DKAhXB1RoKHdmHDqgQ_AUIBigB#t bm=isch&q=welding+robot+comau&imgrc=WtMizS8HWU0PVM%3° (ex. Of robots in this case not in an assembly shop)

STRENGTHS & WEAKNESSES

4.3.1 Strengths - The stations (phases) are decoupled by buffers -> the cycle time is not a constraint; operators are not forced to finish systematically the assembly activities in the given cycle time. - The flexibility is high -> particularly, it is useful when productive mix varies over time in terms of product types and (relative) quantities of product types. o As stations are not coupled, it is possible to plan different routings, so assigning different phases to different (parallel) stations from time to time o Mix, product and expansion flexibility. Mix flexibility means variation in models and volumes related to models (also in automated system => welding tong of robot), Expansion flexibility means expanding the already existing capacity.

4.3.2 Weaknesses - Investment depends on the level of automation of the system and generally the space occupied is higher than the other assembly systems. - It might be difficult to manage the flows of products and components (solution: assembly kits). - The complexity of production planning and control can cause bottlenecks and idle times (comes as a consequence of different product types in the mix and mixed model production to answer to changing demands)

5 ASSEMBLY CELL Assembly cell: suitable solution for the assembly of a medium range of medium volume products

In assembly cells the product moves during assembly through a number of stations with some flexibility in its trajectory (slightly different flows for different products) In manual assembly cells, the organization of work is based on team-work following similar rules and organizational solutions adopted for manufacturing cells Normally in an assembly cell, the operator follows the product being assembled, its mean that the complete assembly process can be made by the operator together with product testing and quality assurance Operators can be given production responsibilities regarding the cell It is easy to allocate to cell the testing and adjusting (and repairing) of assembled product.

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07. Design of assembly lines, cells and shops ex: cell assembly of electro-mechanical products in medium volumes.

Main features of the solution: - Assembly workbench for 2 operators - First operator executes product assembly - Second operator executes the testing and adjusting of the product.

6 ASSEMBLY LINE

GENERAL FEATURES Each assembly line consists of a series of stations where the product is progressively assembled. We are designing a line that is composed by assembly stations, and in each station, we are doing one or more assembly operation; most of the time the activities are made by human or supported by other resources. We have a main assembly flow: the assembly system is moved from one station to another, the squares are the working station in which activities are happening. The activities are physical activities, such as taking component that should be moved to that station in which the component is mounted in the assembly (a kind of WIP) and then moved to another station.

A line is a complex environment with a main flow, working stations in which activities are happening Assembly line is the same concept as manufacturing lines: we have assembly stations and in each of them we are performing one or more assembly operation/task

6.1.1 System description - Every line can be modeled as a series of workstations linked by the rigid transfer system. - The handling system is integrated and could be installed on the roof or on the floor or in between. Thanks to the material handling system, the workpiece visits all the stations in a serial and rigid way. - Every line (which is composed of more workstations) could be involved in the assembly of different types of product (in the example, first line assembles the product α, the second assembles the product δ and the third assembles the product γ), and could be managed as: o single-model line (only one product type); o multi-model line; o mixed-model line (more flexible solution, even if it is always a line). - The entire assembly process is decomposed into elementary assembly tasks, then these tasks are allocated to the stations; the logic of allocation is dictated by certain constraints and/or the optimization of certain objective functions.

6.1.2 Types of product It is a solution chosen for products for which demand is high. Typical examples of assembly lines can be found in the final assembly of automobiles, of electric/electronic components … When some product variety is required, even at high volume, a mixed-model line may be operated as a solution.

6.1.3 System characteristics and criticalities: - Work-force assignment: in a workstation, depending on the complexity of product, one or more operators could work also in this case; again the product may allow this choice or not (e.g. car assembly); - cycle time (CT) is a fundamental parameter for this kind of systems; unlike the fixed position assembly, for assembly lines cycle times are short because each operator executes a small part of the product assembly cycle; representing the time interval between the exit of two consecutive workpieces from the line, it is also the time interval available for the operator to complete his tasks. Hence (starting from requirements) CT can be calculated starting by the requested production capacity P (P has to take into account the value of possible waste): CT = 1/P.

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07. Design of assembly lines, cells and shops

6.1.4 Physical structure and organization of the line: Each station is dedicated to a few tasks, it means that, unlike the fixed position assembly, for assembly lines each station is just equipped with its specific tools, without the need for sharing specific tools/equipment. Unlike the fixed position assembly, in this case necessary components are brought to their corresponding stations, the product being assembled is moved along the line and the finished product is taken from just one specific point (the end point of the line). Therefore, there are just more rational flows, from these two types, of the product being assembled and of the component/part feeding.

EXAMPLES In the 1910‘s, Walter Flanders designed the first assembly line at Henry Ford‘s car factory. The first historical example of assembly line was designed at Henry Ford’s factory in the 1910’s. It represents the first industrial application of Taylor theory. Such theory aimed at splitting the overall complex workload in elementary and simple activities to be allocated to many people.

Ford motor component was the first industry to introduce this model. Till today, we are addressing as “ford production”.

Some historical videos… - https://www.youtube.com/watch?v=QdwH84AT5fU - http://www.history.com/topics/henryford/videos/history-of-the- holidays-the-story-oflabor-day - https://www.youtube.com/watch?v=AgL1ZL_sh08

Today’s assembly line in a factory manufacturing wire harness solutions and electrical assemblies This second example is very different and developed based on principles of lean manufacturing. It is good example; I will not underline much of these principles in theory. In a general sense, it is a good example of an intermittent asynchronous line (buffer size = 1 pallet), with short number of stations (subsequent to the lower complexity of the product in terms of BOM), integration in the line of operations of assembly and quality test… and other clever solutions which can be explained based on the lean manufacturing theory. https://www.youtube.com/watch?v=ovMz2gTjvFA

See these videos - https://www.youtube.com/watch?v=ovMz2gTjvFA - https://www.youtube.com/watch?v=tb_1TrpUrmQ - https://www.youtube.com/watch?v=wR1jETyBl6w - https://www.youtube.com/watch?v=XSrQkdfi1-w - https://www.youtube.com/watch?v=YUzh9PBebsE - https://www.youtube.com/watch?v=6umIEl6Sv8A ex: in the car industry, most of car makers are assembling, they own the factory in which they are doing the final assembly. Ferrari is a special case, because it has also the fabrication work, not just the assembly one. Ferrari is doing its engine, it is not only assembling but also producing some piece, which is not popular in this sector.

The typical Italian company, selling machines, is outsourcing everything apart from the assembling, testing and selling of machines. Assembly is a very important part of manufacturing contests. Other example is textile industries, in which normally material is flowing continuously.

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STRENGTHS - Rationalization of material flows - Low WIP - Limited space requirement - Labour training might be easy - Low cost for workforce

Line is a solution for high volume, featuring efficient and limited cost of operations. An assembly line is a complex system, there a lot of stuff moving, an entire factory in which there are assembling phase, necessary when high productivity is needed; it’s a complex environment also since the right component should arrive at the right time, in the proper position; it should be a production system where everybody is able to work, to use the resources

6.3.1 Rationalization of material flows Material flows are really rationale because each workstation is fed with just its pertinent components; besides, the product being assembled is moved along the line and the finished product is taken from just one specific point (the end point of the line).

6.3.2 Low WIP Unlike the fixed position assembly, in assembly line components are stocked just in correspondence of the afferent stations; moreover, the product being assemble remains at the station just for the duration of a short cycle time (less physical quantities, then less working capital than the fixed position assembly); and when it exits at the end of the line it is soon delivered (to the next logistics activities).

6.3.3 Limited space requirement Obviously, this is directly related to the low WIP. It is also related to the compact and rationale transfer (material handling) system.

6.3.4 Labour training might be easy The line was actually introduced as a solution (applying the Taylor theory) to achieve the goal to make labour training easier (high repetitiveness, few tasks/operations).

6.3.5 Low cost for workforce This is related to the easier labour training: as tasks are standard and repetitive, they do not require high skills, so they do not require highly trained workforce.

WEAKNESSES - Low flexibility - Long time required to start new productions - Repetitive work - Line balancing might be difficult

6.4.1 Low flexibility Line is a solution with the disadvantage, amongst the others, of low flexibility (especially compared to the other types of manual assembly systems). - The line is - by definition - a rigid system linking workstations together: it is a system designed for specific characteristics of the product/product family to assemble (for a limited mix of product types to assemble, if not only one) and for a specific assembly process(es); - thus, it is not easy to introduce new products or to modify the existing line; even a change in product quantities could compromise line operation (generally the more a system is dedicated to a product type, the more its configuration become rigid); - mix flexibility can be managed at some extent, by means of lines which have been properly prepared and designed for such management, i.e. mixed model assembly lines.

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6.4.2 Long time required to start new productions It is connected to the low flexibility, it is equivalent to say a low product flexibility, in terms of product flexibility The introduction of a new product type, assuming that it could be assembled in the existing physical line, requires at least the rebalancing of the stations, a complex problem in general -> see next the difficulties of line balancing in assembly lines (while, in the case of fixed position assembly, for a product introduction it is simpler, as main challenge required is just to train an already versatile workforce).

6.4.3 Repetitive work Operators execute a few tasks which have really brief durations (in terms of minutes) -> it may lead to dissatisfaction (see the case of lines wherein assembly processes are distributed in very small portion to each station -> Ford T).

6.4.4 Line balancing might be difficult Especially for complex products and/or with a large number of variants (when we would aim to operate a mixed model assembly line). Such problem (that is: to allocate the operations considering precedence constraints in the assembly process) concerns not only the design phase (when you need to define the number of stations and to allocate tasks to the workers therein) but also the management phase (when you need to rebalance the line for many reasons, due to some uncertainty on times / changes on times): - product/process improvements induce time variations in assembly processes, or - adaptation to changes in manpower (also day by day, i.e. absenteeism -> rebalance the line; on a longer term, due to the learning process), or - for variations in the production mix, .... Last but not least, in the manual assembly, since operations are performed by human workers, there is the further issue of uncertainty of times: even in case of perfect balancing, the line could have problems because the effective/actual times are different from the theoretical times, due to the natural variability of workers’ activities.

TYPES OF ASSEMBLY LINES There are different types of assembly lines: the concept is always a line of workers, but based on how physical it is, we can have different classifications. Depending on the way the material handling system works, assembly lines can be: - Paced -> there is the same pace in the line - Un-paced -> everything is moved by the worker of single station

6.5.1 Paced line (constrained; always synchronous) In a paced assembly production system typically a common cycle time is given which restricts process times at all stations. The pace is either kept up by a so called - intermittent transport, where the workpiece comes to a full stop at every station, but is automatically transferred as soon as a given time span is elapsed - continuously advancing material handling device, e.g. a conveyor belt, which forces operators to finish their operations before the workpiece has reached the end of the respective station.

In paced line, each station has a certain time amount of work; after it is finished, the assembly is moved to the other stations. The movement is in a rigid way, with the same rhythm; if something is not completed and the machine is moving, the piece won’t be completed (ex: most of car companies use paced line working in continuous way; the intermittent way is used for example by tractor’s industry)

6.5.2 Unpaced line (non-constrained) In unpaced lines, workpieces are transferred whenever the required operations are completed, rather than being bound to a given time span. The operators are doing the work, and when they finished it, they move it to the next stations. It can be further distinguished as to - whether all stations pass on their workpieces simultaneously (synchronous); stations have same rhythm - whether each station decides on transference individually (asynchronous); actions haven’t same duration Under synchronous movement of workpieces, all stations wait for the slowest station to finish all operations before workpieces are transferred at the same point in time.

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PACED LINES Therefore, we can classify the paced lines into 2 categories: - machine-paced lines: the handling system moves automatically products (ex: tractors, Charlie Chaplin) - operator-paced lines: the handling system moves the products only after the operators’ approval

6.6.1 Machine-paced lines The movement of pieces is paced by a timer and given by the cycle time of the line - Workstations are not separated by buffers. - The material handling/transfer system is generally a conveyor which moves the pallet/base where the parts are placed and assembled. - The material handling/transfer system generates an intermittent movement: o during the “transfer” phase, the conveyor moves simultaneously every base/pallet from a station to the following one; o then it stops for a period which lasts the cycle time of the line (this is giving the “pace” of the line -> the time allowed for an operator to work on the job is limited; o during the “stop” phase operators can execute their assigned tasks (and should complete their operations …). - Strengths -> cycle time and production capacity are perfectly controlled Since the handling system moves automatically the pieces, as it starts every regular time given by a timer, there is perfect control of the cycle time, thus there is an accurate control on the production capacity. - Weaknesses -> probability of no completion (at the stations) and problems of unfinished pieces As a consequence of having perfectly controlled cycle times, since manual activities have variable durations, there is no guarantee of the completion of all assembly tasks at the stations, thus there are problems of unfinished pieces (also due to precedence constraints).

At each station/operations cycle, there is the risk/possibility of failing to complete the assigned tasks within the cycle time. This problem is due to the time variability of manual activities (i.e. occasionally the operator could need more time to finish his/her tasks, even if the average time of assigned tasks to the station is lower than the CT, in this scenario the assembly jobs move anyway to the following stations every CT, but the following operators can make only the operations that have precedent operations already done, precedence constraints -> this is limiting their activities in relation to the state of the product being assembled -> it results in an unfinished piece at the end of the line). To avoid the problem of no completion: - a first solution could be the increase of the cycle time, but this implies a reduction of the line production capacity (thus not meeting the target demand); - alternatively, it could be increased the number of stations (to allocate fewer operations / fewer times at each station), this implies the disadvantage of additional costs (i.e. additional installation costs, manpower costs due to more stations, large is the line -> more stations/more WIP/more WIP costs/more space costs, …).

6.6.2 Operator-paced lines The movement of pieces is paced by the operators: the material handling system moves only after all operators have given their approval. A variant of the paced line is the “Operator-paced line”. In such a solution the material handling system doesn’t move automatically the products, it moves them only when all operators involved along the line have are approving (still simultaneous movement but subject to their approval), by pushing a bottom. - Strengths -> no problem of unfinished pieces The possibility for the operators to give their approval before the product moves, eliminates the problem of unfinished pieces. - Weaknesses -> cycle time is variable, and it is determined by the slowest operator Since every worker has to give his approval, cycle time is determined by the slowest operator and it is variable. Each time, the entire line has to wait the slowest station. Therefore, the real cycle time of the line can be longer or shorter than the theoretical one; such variability of the cycle time causes a loss of control on the production capacity -> overall, variations induced in the cycle time/production capacity of the line.

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The risk of giving approval too late compared to the theoretical cycle time: - increases with the operator utilization level (i.e. when the sum of durations of the assembly tasks allocated to a station is close to the theoretical cycle time, risk is higher); - increases with the rise of the number of stations (because having more stations increases the probability of one station leads to a delay).

The ideal solution would be that operators could help each other to minimize the delay generated with respect to the CT (help chain (?)). However this solution requires some additional conditions: - workers should be multi tasking/multi skilled, since they need to be capable to execute other tasks different from their owns, assigned to their stations; - stations should be close, because operators need to reach other stations in a short time; - cycle time should be sufficiently long, because operators need a certain time to provide the help intervention to other stations; - assembled pieces should not be too small, otherwise two operators couldn’t work together on it.

6.6.3 Continuous flow paced lines The material handling system moves at a constant speed and operators follow the piece on which they have to perform the assembly tasks (or they move with it on a platform) - The material handling system moves at a constant and very low speed + Every station is coincident with a (physical) portion (part) of the line (of a length L). - Every time a workpiece – fixed at the handling system – enters a station: o the operator (of the station) goes up the platform where the product is fixed, moves with it within the station while making the assigned assembly tasks, when station ends he / she goes down on the floor and back to the begin of the station; o The operator may stand and move along the station making the assigned assembly tasks, while the assembly is moving; in case of small products, he / she may be sit and move slight movements forewords on the line. - Given the conveyor velocity vc, the distance D between two consecutive pieces (blocked on their respective bases / on the platform) determines the cycle time: CT = D/vc.

The conveyor velocity has to be properly chosen: - so as to allow the execution of the assembly activities while the piece is being moved; - so to be compatible with the maximum space available and physical interference problems between operators; o (maximum space available) if velocity is too high, D, and so line length, would be too high (to guarantee the target demand, i.e. CT); o (physical interference problem) if velocity is too low, D would be too low (to guarantee the target demand, i.e. CT), and operators would not have much room to separate each others (i.e. physical intereference) -> would be too closely working.

Note that the length of a station is a quantity necessarily larger (than) or equal to the distance D: - it can never be smaller than D -> it means giving to operators a time which is at least equal to the cycle time, in order to complete the assigned assembly tasks; - indeed, when L > D, then L > CT * vc → it means the conveyor acts as a buffer → the operator has some extra time to finish his / her activities.

In continuous flow lines, the increase of buffers size (i.e. increase of the stations size / length) implies: - an increase of the actual production capacity due to a decrease of the “unfinished pieces” phenomenon (the theoretical cycle/production capacity is fixed as it is defined by D and vc -> so it is reduced the loss due to unfinished pieces; - even the occupation of more space, longer flow time to traverse the line, and higher WIP level, as there are both pieces within stations and buffers).

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(by comparing to what it is happening in un-paced lines, there was an increase of the actual production capacity due to a decrease of effects of blocking and starvation thanks to better / higher buffer sizes -> i.e. for other reasons, not unfinished pieces, but probability of starvation/blocking -> the actual production capacity is increased).

6.6.4 Continuous flow lines problem In continuous flow lines, since the handling system moves constantly the parts, there is perfect control of the cycle time, thus there is an accurate control on the production capacity. However (as for paced lines), as a consequence of having perfectly controlled cycle times, there is no guarantee of the completion at the stations, thus there are problems of unfinished pieces. As for paced lines, this problem can be solved by introducing the possibility for operators to stop the line, then it is possible to distinguish two cases of continuous flow lines: - Case 1: operators can’t stop the line; - Case 2: operators can stop the line.

6.6.4.1 Case 1: operators can’t stop the line - Strengths -> cycle time and production capacity are perfectly controlled Since the handling system moves constantly and automatically the parts, there is perfect control of the cycle time, thus there is an accurate control on the production capacity. - Weaknesses -> probability of no completion (at the stations) and problems of unfinished pieces As a consequence of having perfectly controlled cycle times, since manual activities have extremely variable durations, there is no guarantee of the completion at the stations, thus there are problems of unfinished pieces.

6.6.4.2 Case 2: operators can stop the line - Strengths -> no problem of unfinished pieces If any problems, the possibility for the operators to stop the line eliminates the issue of unfinished pieces. - Weaknesses -> cycle time and production capacity are not perfectly controlled As operators can stop the line, real cycle time can be longer or shorter than the theoretical one; such variability of the cycle time causes a loss of control on the production capacity, as there is a stoppage of the line commanded by the operator.

UNPACED LINES If a worker is working at a different time than the second worker, between the two persons there will be some material for some periods. It is dynamic system; we should try to anticipate the movement. In a perfect balanced line, each station needs the same time, so the component moves directly from a station to the next one; if it is not balanced, we need some buffers between the stations, where materials are stocked there for a while, waiting for the other station NB: under synchronous movement of workpieces, all stations wait for the slowest station to finish all operations before workpieces are transferred at the same point in time, so there isn’t the necessity of buffers

- Workstations are separated by buffers (where workpieces can be stocked waiting for next operations at downstream workstations). Such buffers should be opportunely sized, they often may represent portions of the transfer system itself (e.g. conveyor belt). - Unlike paced lines, in this case operators are not forced to finish their tasks within the cycle time: occasionally, they can also spend more time to finish them because, while they are still busy in finishing their activities, buffers avoid line stoppages because they enable to feed downstream stations with the already stocked pieces and provide room to stock pieces produced from upstream stations.

NB: clearly operators can’t systematically exceed the cycle time, otherwise downstream buffers would result empty and/or upstream buffers would result full. Which means stopping the production of respective stations (up/downwards) and, by propagating to the bottleneck station, a reduced production capacity of the line.

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More precisely, since buffers have finite capacity, two kinds of problems could happen: - problem of blocking: when a buffer is full the upstream station can’t drop the piece (having finished its assigned task on the current piece); - problem of starvation: when a buffer is empty the downstream station can’t take a new piece (having finished its assigned task on the current piece).

If these events are frequent, there is a risk for the reduction of the line production capacity. The frequency (of such events) depends on: - the sizing of buffers -> for this reason it is important –during the design of the line- to size buffers correctly (to reduce probability of blocking/starvation); - the balancing of the line (the presence of stations overloaded with work increases the frequency of these events directly down and upstream).

6.7.1 Strengths - no problem of unfinished pieces thanks to the presence of buffers, which decouples operations at different stations and thus allows to conclude the tasks at each station. - cycle time can be exceeded, but only occasionally (i.e. problems of blocking and starvation) thanks to the presence of buffers, operators are not forced to finish their tasks always within the cycle time: occasionally they can also spend more time to finish them because, while they are still busy in finishing their activities, buffers avoid line stoppages because they feed downstream stations with the stocked pieces….. etc. Clearly, they can’t systematically exceed the cycle time, otherwise downstream buffers would result empty and/or upstream buffers would result full.

6.7.2 Weaknesses Cycle time and production capacity are not perfectly controlled The cycle time depends (on average) on the bottleneck’s operator/station, which then limits the production capacity; the propagation of blocking and starvation may affect the cycle time of the line, i.e. affecting the bottleneck; but this depends on the sizing of buffers, that can reduce (or not) the probability of blocking or starvation; this adds to the natural variability of the bottleneck itself.

6.7.3 Examples

PC assembly - intermittent, asynchronous - conveyor through which the operator, sitting in his / her work bench, pushed the assembled piece downard - material feeding done on the other side of the workbench (the one not adjacent to the line.

Different solutions in the automotive sector of continuous flow line: - Cabin truck (the cabin or cab of a truck is an enclosed space in a truck where the driver is seated) is moved on a platform and the operator is seated in the cab to make the assembly task - Car assembly – car body has already painted (in a paint shop) is now subject to a final assembly; the operator standing by the line is making the assigned operations / car door assembly similar solutions but as a preassembly In both cases - components are stocked on the back along the line/station - the transporter is an overhead conveyor for car bodies http://www.bmwgroup.com/e/0_0_www_bmwgroup_com/produktion/fahrzeugfertigung/automobilfertigung/erlebnis_produktion/prod_prozesse.shtml

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7 DESIGN OF A MANUAL ASSEMBLY LINE - Definition of the balancing constraints - Evaluation of the time of each assembly operation - Calculation of the cycle time The design consists of Assembly Line Balancing (ALB) For this type of systems, the design also consists in determining the number of stations which constitute the line. The first step is to identify the production mix: quantities and types of products to realize during the expected useful life of the line. For the sake of simplicity, we now refer to the single-model line. We need to know the target demand.

It is necessary to identify/define the balancing constraints. Such constraints are: - Cycle time - Precedence relationships among operations - Incompatibility between operations that cannot be assigned to the same station - Opportunity or necessity to assign some operations to the same station - Constraints related to space - Constraints related to workers - Constraints related to the material feeding

SHORT INTRO ON CONSTRAINTS (INPUTS) 7.1.1 Input 1 One of the most used method to define the precedence relationships among operations is drawing an Assembly Graph. Such graph determines the constraints to be taken into account when balancing the line: precedence relationships (i.e. arcs) b/w operations (i.e. nodes) have to be considered both within the stations and between successive stations. Two other methods are: the Hoffman matrix or a precedence table.

7.1.2 Input 2 Afterwards, it is necessary to define/evaluate the time of each assembly operation/task. Since durations are not deterministic, they are difficult to be determined (unlike parts production lines). There are 2 different methods to evaluate the time of each assembly operation: - using the MTM (Motion Time Measurement) approach, which using appropriate tables, allows to calculate durations of assembly operations. This method decomposes the manual operation into the basic motions or human movements required to perform it, and assigns to each motion a predetermined standard time which is determined by the nature of the motion and the conditions under which it is made; when all such times are added up, it provides standard time for the assembly operation/task; standard times can be finally determined by adding suitable allowances (which take into account fatigue and working conditions of the operator). This approach is: o time consuming and expensive; o accurate. - observing and measuring by means of a chronometer the execution of an operation for a certain number of times, then calculating the mean value and standard deviation. This approach is: o time consuming as the number of times must be sufficiently high to guarantee the statistical significance of the summary statistics; o allows to have reliable estimations (since it is calculated based on selected operators). Independently from the evaluation method, this step allows to associate to every operation its mean execution time and standard deviation. https://www.youtube.com/watch?v=k9vIhPszb2I

7.1.3 Input 3 Knowing the requested production capacity (P) due to the target demand, it is then possible to calculate the requested cycle time: CT = 1/P -> in ALB type 1 CT is a constraint/input

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7.1.4 Design problem Afterwards it is necessary to balance the line (assembly line balancing – ALB): to allocate the operations to the different stations, respecting constraints and considering specific objectives. It is then known the required number of stations as well as the operations assigned to each station.

When solving ALB, it is possible to size the workforce: the number of operators doesn’t necessarily coincide with the number of stations. - it could be decided to have more operators in certain stations (possible in case of bulky products) -> parallelization of resources; - It could be decided to use a pool of jolly operators (to replace workers of the line when they have a break); - it should be decided a pool of workers considering absenteeism, illness.

This is a generic model. In particular the assembly line balancing is an activity equally important for all the types of assembly lines. Obviously, there are instead specific aspects which should be considered when dealing with particular types, for instance: - in un-paced lines buffers must be correctly sized, to guarantee an adequate decoupling of operations b/w stations; - in continuous flow lines the length of every station (i.e. buffers) and conveyor velocity must be defined.

7.1.5 Assembly process Example of definition of the balancing constraints: - the precedence relationships among operations (which are synthesized in the table) in this example are showed by the Assembly Graph; - the assembly process table is a useful and immediate tool which is helpful during the design phase, for consultation of predetermined data ….

7.1.6 Number of single sites/stations In an unbalanced system, not synchronous system, there need be space between a station and the next station, there could be buffer which should be designed: how many square meters? The number of stations Nj for the product j can be calculated as follows: 푁푗 = 푃퐶푗 푥 푇푗 where: - 푃퐶푗 = requested production capacity for product-type j [pieces/h], the expected cycle time - 푇푗 = time required in order to complete the assembly process on a piece of product-type j [h/piece] ex: how many people do I need to build many chairs [We will not put a safety coefficient]

BALANCING CONSTRAINTS 7.2.1 Respect the cycle time The workload at each station (due to the allocated operations) cannot exceed the cycle time, otherwise production capacity is affected. E.g. 1 machine-paced lines -> high number of unfinished pieces E.g. 2 un-paced lined: the average time of the bottleneck > CT so not respect of requested PC

7.2.2 Respect the relationships among operations technological constraints due to the assembly process enforce to execute some operations before others (as already seen the most common way to represent relationships is using an Assembly Graph).

7.2.3 Incompatibility between operations that cannot be assigned to the same station (negative zoning) - to safety problems; it is better to split into more stations the operations requiring consecutive tasks (that are) dangerous because of non-compatible characteristics, e.g. cleaning using a flammable solvent is not compatible with welding. - to logistics problems due to the size of the components/tools involved by the assembly operations; for instance, operations which require different and bulky tools should be split into more stations in order to avoid creating stations exceeding some “standard”/reference dimensions.

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7.2.4 Opportunity or necessity to assign some operations to the same station (positive zoning) - operations which share the same used tools / equipment (especially when they are particularly expensive -> no duplication); - operations which share the same required positioning of a bulky / heavy product; operations should be grouped to avoid excessive handling for re-positioning (i.e. operations in the bottom part of a machine -> using a lift”). - Constraints related to space; in most cases the available space is limited, the assembly line is frequently built in existing buildings. - Constraints related to workers; some workers could not have the required skills or experience (i.e. different qualifications) for certain operations (especially in case of complex products). - Constraints related to material feeding (materials flow management); for instance materials requiring an overhead conveyor to be handled should be grouped in a few stations so we may use in a minimum number of stations this structure.

BALANCING OBJECTIVES In reality, ALB problem can be solved, subject to constraints, and with reference to different objectives: - technical objectives - economic objectives (unlike the technical ones, these explicitly consider cost data)

7.3.1 Technical objectives - Minimizing the number of stations, given the where: cycle time - n = number of stations - Minimizing the cycle time, given the number - CT = cycle time of stations - N = number of assembly operations - Minimizing the total idle time - ti= time to perform operation i (i.e. unit 푁 퐼푇 = 푛 ∗ 퐶푇 − ∑푖=1 푡푖 working time)

- Minimizing the number of stations, given the cycle time as constraint (1st type ALB – Assembly Line Balancing problem) This is the most frequent case in practice: given the cycle time (determined by the requested production capacity), it is minimized the total number of stations (therefore it is minimized the total number of operators, which is a cost item). - Minimizing the cycle time, given the number of stations (2nd type ALB – Assembly Line Balancing problem) This case is not at all frequent in reality: given the number of stations, it is minimized the cycle time, therefore it is maximized the production capacity. - Minimizing the total idle time The total idle time IT is a residual/remaining time (explain the meaning, e.g. case of paced line, N stations each of them has the time allowed for an operator to work while the sum is the total time required to make the assembly) -> it represents the time not used in order to execute assembly operations. Minimizing the total idle time means solving one of the two problems: 1st type ALB or 2nd type ALB, precisely: o Given the cycle time, minimizing the total idle time means minimizing the total number of stations (since the sum of the times needed to perform the required operations, depending on the technology used for the assembly, is fixed); o Given the number of stations, minimizing the total idle time means minimizing the cycle time.

These objectives are two sides of the same coin - Minimizing the probability of no completion o in a machine-paced line, or o in a continuous flow line, in case the operator can’t stop the line - Minimizing the probability that the times of operations in one or more stations exceeds CT o in an operator-paced line, or o in a continuous flow line, in case the operator can stop the line.

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Minimizing this type of objective function can lead to unsatisfactory results, particularly: - in situations where the cycle time is given (ALB 1st type), it is likely to generate a number of stations excessively high (deciding for having a lower number of operations – to avoid unfinished operations – allocated to each station, therefore a lower probability of no completion / of stopping the line is obtained -> means an higher number of stations); - in situations where the number of stations is given (ALB 2nd type), it is likely to generate an excessively high cycle time (and consequently an insufficient production capacity) as we would like to give higher CT with respect to the time of the assigned operations).

7.3.2 Economic objectives Every time that we add a station to the line, I have to consider the cost related to the new personnel, the longer conveyor and most powerful engine to move it Minimizing the total expected cost (TEC) 푇퐸퐶 = 퐿퐶 + 퐸_퐶푈푇 - LC = line cost (equipment cost + operators cost) - E_CUT = expected cost of unfinished operations (i.e. tasks)

The following assumptions may be introduced: - the unfinished subassembly continues to proceed along the line, then workers perform only the operations which are not affected by non-completion / unfinished operations other cases may be possible to manage the unfinished operations; - at each station only one operator works other cases may happen with more operators in the same station (parallelization).

Since we are talking about unfinished operations, this objective applies only for machine-paced lines or in continuous flow lines. - LC = line cost (equipment cost + operators cost): o operator cost depends on the number of shifts; o equipment cost depends on the installed facilities. LC is proportional to the number of stations (in realty this relationship is not linear because in one station could work more than one operator or because of jolly operators … etc.). - E_CUT = expected cost of unfinished operations (i.e. tasks)

The cost of unfinished operations is the cost associated with the scenario in which unfinished operations occur. It represents an “expected” cost because it has a probability of occurrence (it means that the cost has to be multiplied for this probability).

푬_푪푼푻 = ∑(푷풌 ∗ 푪풌) 풌 Ck is the cost associated with the completion of the operations not completed in a station (not completed because the operator at a station has not finished his operation k within the cycle time / length of the station + other operations allocated cannot be executed because of the no-completion of operation k, for reason of precedence constraints). - Note that each operation k has a Pk is the probability of no-completion, then a Tk (time to complete), then a Ck (cost to complete off-line - Note that the execution off-line is costing as it required flexibility from operators -> highly qualified / fixed position assembly

There is a trade-off between the line cost (LC) and the expected cost of unfinished operations (E_CUT): - It is possible to reduce the probability of no completion (then the related costs, E_CUT), by reducing operators utilization - which means to increase the number of stations and/or the cycle time (ALB 1st or 2nd type). Consequently, there is an increase of the line cost (LC). - It is possible to reduce the line cost (LC), increasing operators’ utilization which means to reduce the number of stations and/or the cycle time (ALB 1st or 2nd type). Consequently, there is an increase of the probability of unfinished pieces (then E_CUT increases).

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The objective of minimizing the total expected cost allows to overcome the limitations related to previously described technical objectives: the optimization of the 1st type ALB problem or the 2nd type ALB problem or the minimization of the total idle time produce solutions leading to a solution on the left side of drawn diagram: they find solutions which correspond to the choice of lower numbers of stations i.e. (higher saturation/utilization) such as to have lower line costs (LC). But, looking at the graph it is evident that, from the total expected cost point of view, none of the solutions placed on the left side is the best. TEC is minimized at the intermediate values of number of stations (hence intermediate utilization).

Regarding the unfinished subassemblies management policy, it is possible to identify different cases, each of them determines different values of the cost of unfinished operations: - the unfinished subassembly continues to proceed along the line, then in the downstream stations, only the operations not affected by no-completion are executed (in the assembly graph operations, that are NOT directly or indirectly connected to the unfinished operation); therefore the piece needs to be finished after its exit from the line, in a “hospital station”; - the unfinished subassembly is immediately removed from the line and finished in a “hospital station”; this solution -as the previous one- implies the operating costs corresponding to the “hospital station”; - if in a station the cycle time is exceeded, the line is stopped until the completion of the operations; in this case costs are generated by the opportunity cost linked to the decrease of the production capacity. This policy is typical for Just in Time systems, because it allows greater quality control (unfinished items are not moved) and advantages in terms of time (no extra work to finish operations). Moreover, in JIT systems, time variability is reduced by the presence of multitasking operators since they help each other (an operator who has already finished his operations can help another who is nearby); - there are “jolly operators”, who can intervene when some other operator needs help; in this case the cost is generated by the presence of the “jolly operators”; there are multi-skilled operators which can help adjacent operators (i.e. if they have finished their assigned tasks).

LINE BALANCING – PROBABILITY OF NO-COMPLETION We have a list of operations with a cycle time and we can assign operations to stations, according to different methods, as we did in the normal lines. Since we are assembling, we are dealing with humans: they can be described in terms of P and standard deviation. Based on this assumption, there is this model based on the fixed utilization, called “probability of not completion”, which means the probability of not finishing a product ex: we are in the assembly line, we are assembling a certain component in a certain subassembly phase in a paced system, and I should be able to assemble the component in the five minutes given; if I cannot finish the component, the line is generating a component not finished (this is happening also in the car industry: there is a uncomplete final products) -> what should I do to complete?

∗ For each task the following constraint has to be satisfied: 푃푘 ≤ 푃 where: - Pk = probability of no-completion of task k - P* = maximum probability of no-completion

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Method III: Managing the probability of no-completion This method has some analogies with the method of the maximum value of utilization rate of operators imposed as a design criterion. For each task this constraint has to be satisfied: Pk ≤ P* In fixing the value of P*, it must be considered that: - fixing a value too low implies: o high number of stations or, in other words, high line cost (LC); o low expected cost of unfinished operations (E_CUT) - fixing a value too high implies: o low line cost (LC) o high expected cost of unfinished operations (E_CUT)

Starting point: the line doesn’t exist. Then, it is created the first station: considering an operation/task which has not precedence constraints, it is calculated its probability of no-completion (Pk) and, if it is lower than P* (if this condition is not verified for the first assigned operation, the problem doesn’t have a feasible solution), this operation is allocated to the station. Afterwards, checking that precedence constraints are fulfilled, another operation is considered: - if its Pk summed to the previous Pk is still ≤ P*, the new operation is allocated to the same station. Then another operation is considered and it is verified the possibility to allocate it to the same station (again, verifying the precedence constraints and the Pk ≤ P* constraint) . - if its Pk summed to the previous Pk is not ≤ P*, it is created another station and the operation is allocated to the new station. The procedure ends when all the operations of the assembly graph have been assigned to stations.

7.4.1 Characteristic of this method: - (+) it is quite simple, even if probability calculations make it more complex (-) than the method of the maximum value of utilization rate imposed - (+) it considers the uncertainty / variability of the times required to perform operations (unlike the method of the maximum value of utilization imposed in which deterministic times are hypothesized); - its other characteristics are similar to those of the method of the maximum value of utilization imposed

It is hypothesized that times Ti are random variables: they follow a normal distribution and they are independent from each other. Ti ~ N(ti, σi).

7.4.2 Steps of the method: 14. Calculate the remaining time related to task k 15. Calculate the variable associated to the remaining time 16. Calculate the probability of completion 17. Calculate the probability of no completion

Firstly I have to assign the long list of operation, we have to select operation to be assigned to the stations, trying to use more cycle time, to increase the speed of the line and minimize the idle time, which is the time not used in the line.

18. Calculate the remaining time related to task k 푅푇푘 = 퐶푇 − ∑푖∈푆 푡푖 where: - CT = cycle time - ti = mean time of task i (time required to perform task i) - S = set of tasks assigned to the operator (task k included) RTk = remaining time -> it is the mean remaining time after the operation k is assigned

푅푇푘 19. Calculate the variable associated to the remaining time: 푍푘 = 2 √∑푖∈푆 σ푖 where σi = standard deviation of the time required to perform task i

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20. Φ(Zk) is the probability of completion Standard normal distribution For normal distribution: - 푃(∑푖∈푆 푇푖 ≤ 퐶푇) probability of completion - 1 − 푃(∑푖∈푆 푇푖 ≤ 퐶푇) probability of no-completion

21. Therefore, the probability of no-completion is 푃푘 = 1– 훷(푍푘)

7.4.3 Values of Φ(Zk)

7.4.4 Demonstration of the relation Pk = 1 – Φ(Zk) The probability of no-completion is the probability that the operator spends a time to perform its operations/tasks that is longer than the cycle time: 2 2 P (∑iєs Ti > CT) = 1 – P(∑iєs Ti ≤ CT) = 1 – P( ((∑iєs Ti – ∑iєs ti )/√∑iєs σi )≤((TC – ∑iєs ti )/√∑iєs σi )) ) Thanks to the hypothesis of independence of the Ti variables, if it results: 2 ∑iєs Ti ~ N(∑iєs ti ; √∑iєs σi ) Then: 2 ∑iєs (Ti – ∑iєs ti )/√∑iєs σi ~ N(0,1) And so, it follows that: 2 2 Pk = P (∑iєs Ti > CT) = 1 – Φ((TC – ∑iєs ti )/√∑iєs σi )) = 1- Φ(TRk /√∑iєs σi ) = 1 – Φ(Zk) The independency allows to sum the standard deviations.

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7.4.5 Example

I have assigned 4 operation; I know the average time and st. dev. for each of them (obtained by collecting data) The P* is a decision, the CT is given We have to calculate the PI

If it is overcoming the threshold of P*: - it is possible to accept it → implies the choice of an higher expected cost of unfinished operations (E_CUT) … but this may be not unacceptable (it may be acceptable when it induces low increase of Pk, especially with additional operations with low std. deviations) - it is possible to parallelize stations → it doesn’t just solve the problem but it also allows to exploit other opportunities (see previous examples) -> that is: relaxing constraints may mean also giving more possibilities in order to better assign/optimize assignment in a station, thus reducing / accommodating probabilities of no completion.

8 MANUAL ASSEMBLY SYSTEMS

GENERAL FEATURES In recent times, the need to offer diversified products (product differentiation as business strategy, products with different variants / optionals offered to the market) has strongly affected assembly systems. There are 3 possible configurations (involving different kinds of production mix management): - Single-model (more lines, one for each product); - Multi-model; - Mixed-model.

SINGLE MODEL It is the most immediate solution: there is one dedicated assembly line for each product model to be assembled. It is adequate when the production volumes are high and stable. Main characteristics of this solution are: - low flexibility: each line is dedicated to a single product type; any kind of change, both in product features and in product quantities, can lead to heavy changes in the line design (rebalancing/reconfiguration); - easy management: since each line assembles a single product type/model, there is no complexity in managing flows of materials (i.e. managing flows of the different components required in accordance to the product model) and information (operators need NOT to be informed about tasks to be performed, no new instructions as the model is always the same).

MULTI-MODEL We are dealing with a multi model if in a line (both paced and un-paced) we have to consider different types of product in the same product family. Moving from single model to multi model the complexity is increasing (and moving to mixed model is more difficult)

8.3.1 General features - Products are made in batches -> first triangles, then squares and then circle; always belonging to the same product family; I should pay attention to have all the component needed for the different batches - Model variations can be wide - Problems o Keeping high inventories, typical of batch production o Determining the cycle time and the number of stations related to each model o Determining the batch size and sequence in which the different models have to be launched onto the line

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The line can assemble more than one product type (more than one model / variant). Anyway, products are managed in batches since their setups are relevant in cost and time (i.e. setups consist primarily of replacing components). As a consequence, along the line, it is not possible that two different products are assembled at the same time (except in transients when changing the product types with no line stoppage).

Main characteristics of this solution: - batch sizing and sequencing: batches need to be properly sized and sequenced; batch sizing = f(inventory holding costs, setup costs); batch sequencing may be sequence dependent, when changing from one product model to the other; to size batches it has to be considered the trade-off between stock costs and setup costs: o small size batches determine low stock levels, but they force to make frequent setups; conversely, choice of big size batches determines inventory holding costs; o sequencing has to take into account the total setup time (if the setup time depends on the sequence) and the loss of production capacity due to the change over from a product to another. - cycle time and number of stations dependent on the product type to be assembled -> if the number of stations changes a lot depending on the particular product type, there may be sizing and manpower issues; you should find a compromise in solutions; it can happen that there may be high differences in the number of stations required by each product model (problem setting: given their requested CT, determine the number of stations) as the time requirements are different-> problem in number of operators / their excess; - high stock of finished product as, due to high set-up, this kind of line doesn’t allow to precisely follow the demand (unlike mixed-model assembly lines), the more batches are big, the more stocks are high; it is not possible to change the production rate; inventory are higher as higher batch size are required.

8.3.2 Set-up of multi-model lines: - primarily due to time needed to replace components as stocks of parts in the stations / equipment in the stations, when the line is stopped to change as well as to provide new instructions to operators: o time to change components low if product models in sequence are very similar -> leading to similar components required by the station; high if product models are very different > high opportunity cost due to the line stoppage; o sequencing is important for setup time reduction, as it may reduce the opportunity cost due to the line stoppage (no big changes are required, the time is short with a product changeover). E.g. un-paced lines https://www.youtube.com/watch?v=ovMz2gTjvFA for example different lengths of wire harness solutions and electrical assemblies may change some raw components, the equipment used to join the wires etc. adjusting to the length … -> we have to stop, not to interfere with line operators.

- consider also the effects of transient subsequent to set-up, when you stop or not the line (in order to empty the line with the old product model / to fill it with the new product model): E.g. un-paced line from A to B; if done while the line is stopped (not in shadow time) transient is 30 minutes x WIP to empty the line + 25 minutes x Number of stations (when line is stopped); if stopped, 30 minutes x WIP to empty the line + 25 minutes x Last station (when line is not stopped); it should be possible to change components during the line run (changing progressively); we save time for the transient; any way, there is a production lost due to bottleneck effect -> e.g. in an un-paced line, 25 minutes, thus quicker than 30 -> leads to WIP building -> approaching blocking -> risk of stopping operations of a station due to blocking in the future -> this will be paid later, as we have seen, in a balanced line, it corresponds to a lost capacity E.g. again un-paced lines with common components / equipment, change in shadow time progressively from the first station on while changeover is being applied (from A to B), e.g. the change of components can be made along the side of the line that is free from installation (see the PC asm line)

- Some other examples of changes may regard reconfiguration of the line as: o Rearranging number of stations (when it is possible as the installation can be reconfiguration, e.g. of simple tables work benches); o Changing parameters, e.g. distance b/w pieces in a continuous flow line, timer of the machine- paced line;

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8.3.3 Multi-model line balancing The balancing of multi-model lines can be seen as the balancing of single-model line (mono-product) since the line assembles a single product type at a time (a batch of product type is produced). Except for the transient it is exactly producing a single model. The balancing procedure consists of 5 steps: 22. Calculate the minimum number of stations of the line (taking into account all the product types) 23. Calculate the cycle time for each model / product type j 24. Balance the line for each model j and determine the number of stations Kj** 25. Adjust the line balancing if needed (e.g. keeping the same number of stations for all models) 26. Verify the feasibility of the solution w.r.t. available working time

The line should be design in order to be good enough for one batch and all the other batches. In this model we should firstly have a rough idea of the number of stations ∑푗 푄푗∗∑푖∈푆 푇푖푗 27. Calculate the minimum number of stations of the line 퐾∗ = 푗 where: 퐻∗α - Qj = quantity of model j (yearly demand) - Sj = set of tasks related to model j - Tij = mean time of task i of model j - H = number of available hours (available time) - α = maximum value of the utilization rate (0 < α <= 1)

The relation (above) has validity if at each station there is only one operator. - The numerator is the total time required to produce the whole range of products (since it is the sum - considering the needed quantities of each product- of all the times required to assemble each product model). - The previously described relation K* = T/CT *  is equivalent to this one, since it still represents the ratio: required workload / available time, but in this case, it is calculated along the year (the previous one was per product). The K* is just the minimum value from which to start. - Note that CT = H / Qj, so it is the requested CT, hence it comes out the equivalence in case of single product type. - K* (the minimum number of stations) is calculated for all models because it is important to keep a sufficiently high utilization of operators (which decreases when this number increases).

∑푖∈푆 푇푖푗 28. Calculate the cycle time for each model j 퐶푇 = 푗 푗 퐾∗∗α

29. Balance the line for each model j and determine the number of stations Kj** We should try to design the line for the first product model, and then for the second and so on Since the line balancing is based on the cycle times TCj calculated in the previous step (2), for each model j the balancing is performed using any algorithm among those seen for mono-product lines. - app of the algorithm is done to minimize the number of stations/expected cost of the line (considering also probability of no completion), given cycle time as constraint (1st type ALB – Assembly Line Balancing problem); - the number of stations may be different for each product model j, which means the need of an adjustment, when reconfiguration of number of stations is not possible / not desirable (i.e. not desirable -> effect on workers -> if it is decided a lower number of stations, a surplus of workers for products with low time requirements happens -> should be reallocated).

30. Adjust the line balancing if needed (e.g. keeping the same number of stations for all models), through some corrective measures on the results obtained in step 3 ex: we have designed the line for product 1 and I got 5 station, for the second model I need 6 station; if you want to use the same line for the two products, what will you do? You will pick 5 or 6 station? We have to deal with adjustments, and then we should evaluate the time (I have to consider also the setup time) and the cost of the two alternatives

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E.g.1 For a machine paced line -> let’s say that the result is K1** = 10 e K2** = 15. We keep 15, so we redistribute operations of 1 amongst 15. We can now have for sure a low UR, we could reduce the CT (by changing the timer) and make operations quickly at line level (obtain the Qj in lower planned time); this avoids some too low UR of operators, w/o increasing much the prob of no completion. E.g.2 for an un-paced line -> reduced times assigned for each station with higher number of stations than required -> low CT, high PC, low time to reach the Qj

31. Verify the feasibility of the solution ∑푖 푄푖 ∗ 퐶푇푗 + ∑푗 푆푈푇푗 ∗ 푁퐵푗 ≤ 퐻 where: - SUTj = setup time related to model j - NBj = number of batches of model j The necessary work capacity has to be equal to the available work capacity, considering all set-ups. NB: verification also regards transient periods when models are changed (dependent on production sequencing)

MIXED-MODEL 8.4.1 General features - Different models can be assembled simultaneously without batching - Production rates of different models can be adjusted as product demand changes - Problems o Reducing / eliminating setup o Getting the right components to each station for the model currently there o Determining the sequence in which different models have to be launched onto the line o Managing flows when parallel stations are used

The line can assemble more than one product type and there is no need to manage products in separate batches owing to the strong reduction in setup times. It is possible to realize sequences of product types totally different from each other (even achieving the unitary batch size, that is now possible). Typically, this solution is associated to continuous flow lines or un-paced lines. Instead, it is not associable to paced lines because the cycle time should be, in this case, fixed to the longest assembly time / cycle time sought among all the assembled product types (to be able to conclude in this time window all the operations assigned); then, it would lead to a loss in production capacity because such cycle time would be too long for the majority of the product types.

Main characteristics of this solution: - possibility to follow the demand: it is possible to produce the required products within a very short period of time, then the stock of finished products is low thanks to limited batch sizes (for this reason mixed-model lines are highly used in “just in time” contexts); - need to reduce setup times to systematically and precisely follow the demand; to reach this goal not only products and processes need to be suitably designed, but also the line needs to be properly balanced; - need for an appropriate sequencing of the models. It is a fundamental problem because it affects not only the line performances (i.e. influent for PC losses in un-paced lines or for the probability of no completion in continuous flow lines), but also the performances of the upstream systems (internal departments and suppliers) and the downstream systems (distribution system) - difficult components’ flow management. As the line can assemble more than one product type, each station has to be fed with all possible components which could be required for each specific product model (this complexity increases with the increase of the product types); operations and components required are changing and this builds complexity in the component logistics. Solutions could be: o use of small station warehouses, periodically fed (this solution is suitable for small components); o use of assembly kits (that are prepared upstream the line), which contain components associated to specific products: they go ahead along the line together with the corresponding product which is being assembled. o use of overhead conveyors (in particular for large components). - difficult parallel stations management: the presence of parallel stations could modify the sequence of production because of the variability associated to operation times (this complexity increases when the synchronization of the feeding of the stations depends on the sequence imposed at the beginning of the line). A solution to this problem could be preparing a buffer upstream parallel stations to restore the initial sequence.

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8.4.2 Production sequencing - Objectives: 32. minimizing the probability of no completion, which is indirectly reached when tasks are completed as soon as possible.

In the example it has been defined: - station length (L) and conveyor speed (V), with those parameters FT= L/V= 4 min. - CT= 2 min. - time to assemble the model A, which is 1 min. time to assemble the model B, which is 3 min. - the required production mix: 3 units of the model A and 3 units of the model B. REMARK: the cycle time constraint is respected because at each cycle time, on average, the operator needs 2 minutes for the production mix: (3*1+3*3)/5) = 2 min.

This example is simplified because it doesn’t consider the duration of setup times. - CASE 1: The bad sequencing leads to a no-completion. This is due to the choice to assemble at first the product model (A) with shortest assembly time and after the other one (B) - CASE 2: The sequencing is better than CASE 1, even if at the fourth unit there is the danger / risk of no completion (remember that assembly times are aleatory). - CASE 3: The sequencing is optimal. The operator finishes always his tasks with a safety (time) buffer, then the probability of no completion is minimized. This solution contemplates the alternation of models: in this way the operator has always the possibility to recover the time spent to assemble the model which requires more time (B) at the following cycle (assembling the model which requires less time).

33. Keeping a constant rate of usage of all components used by the line In “just in time contexts” it is important to avoid fluctuations of any type of demands. In particular, referring to the final assembly line, it is important to guarantee a levelled use of parts and components provided by the upstream departments: it is then useful to establish sequences which allow to satisfy this condition.

8.4.3 Line balancing - Objectives The balancing problem in mixed-model lines has some specific issues which make it more difficult than the balancing problem in multi-model lines. Anyway, the main objectives are the same (already seen in multi-model lines): - Minimizing the number of stations, given the cycle time (line balancing); once defined the production mix (required models and their demands), the objective is to minimize the number of stations, then to minimize setup costs, labor costs, etc. - Minimizing the probability of no completion (station balancing) in this case the objective is to minimize the no-completion phenomena in the stations. Generally, particular objective functions are used for allowing to indirectly minimize such phenomena.

8.4.3.1 Example – station balancing:

(it has been taken the worst sequencing case of the previous example to simplify the understanding of the value of the station balancing)

In the first case (Case 1), the assembly time of the model A is 1 min. and the assembly time of the model B is 3 min. It represents the case of bad station balancing: when the first model (A) arrives at the station, the operator works on it for 1 min., he goes back to the upstream boundary of the station and he is forced to wait for a minute (since the cycle time is 2 min.) the arrive of the second unit of model A. Problems begin when the second model (B) arrives at the station: its assembly time is 3 min., then when the operator finishes to work on the first unit, the second unit B has already got in the station and he finishes to work on it in correspondence with the downstream boundary of the station. Clearly, the third unit B incurs the no-completion phenomenon. The causes which have led to the no-completion are two: - the great difference between the assembly times of the two models; - the production sequence (see the previous example).

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In the second case (Case 2) the production sequence is the same of Case 1. Even CT, station length and the overall workload of the station are unchanged. However, in this case, the assembly times are changed (better uniformity): the assembly time of the model A is 1,5 min. and the assembly time of the model B is 2,5 min. This change allows to avoid the no-completion phenomenon, thanks to the better station balancing.

8.4.3.2 Steps 34. Calculate the Balancing Index within the stations (station balancing) 2 √∑푀 (푡 −∑푀 푡 ∗α) 푆푇 푗=1 푗푘 푤=1 푤푘 퐵퐼푤푖푡ℎ푖푛 푡ℎ푒 푠푡푎푡푖표푛푠 = ∑푘=1 푀 where ∑푗=1 푡푗푘∗α - k = index of the station - j, w= index of the model - ST = number of stations - M= number of different models - tjk= mean time of the tasks of model j assigned to station k - Qj = quantity of model j that has to be produced 푀 - Q = total quantity that has to be produced (∑푗=1 푄푗) 푄 - 훼 = share dedicated to model j within the total quantity 훼 = 푗 (similarly 훼 ) 푗 푗 푄 푤

Technical objectives: lower the BI, better the balance within each line station To balance stations, it has to be minimized this objective function (above). - ∑twk*αw is the mean weighted time assigned to station k, weights are given by the required quantities of each model; - therefore tjk - ∑twk*αw is the variation between the time required for the model j at the station k and the mean weighted time which the station has to process. This term is squared to avoid compensations. - the denominator ∑twk*αw normalizes the result. 푇푀 2 35. Calculate the Balancing Index along the line 퐵퐼 = √∑푆푇 (푇푀 − ∑푆푇 푦) 푎푙표푛𝑔 푡ℎ푒 푙푖푛푒 푘=1 푘 푦=1 푆푇 푀 where 푇푀푘 = ∑푗=1 푡푗푘 ∗ α푗

Technical objectives: lower the BI, better the balance along the line To balance the line, it has to be minimized this objective function (above). Line balancing -> tasks have to be assigned to each station in a way that balances the workload between stations. - TMk is the mean workload of the station k; - ST is the number of stations - TMk - ∑(TMy / ST) is the variation between the workload of the station k and an “ideal” workload of the stations (obtained if you uniformly distribute the workload between stations).

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9 DESIGN OF UNPACED LINES - BUFFER SIZE Buffers allow for partial independence between the stations, thereby protecting the line against assembly time variability.

9.1.1 Buffers between stations: - are inter-operational, with the function to decouple the operations in the stations; - provide space to hold a certain number of pieces; - correspond to portion of the material handling system.

9.1.2 Decoupling function Due to the decoupling function, an operator in a station can occasionally exceed (go beyond) the CT (i.e. the requested CT in order to reach the target PC), as the station downward and upward can continue their operations, respectively thanks to the material available on progress (i.e. downward can be fed by a new piece) and the remaining space / capacity of the buffer (i.e. upward can drop the piece).

NB: Since buffers have finite capacity, two kinds of problems could happen (when a station up/downward finishes its operations): - problem of blocking: when a buffer is full the upstream station can’t drop the piece; - problem of starvation: when a buffer is empty the downstream station can’t take the piece. If these events are frequent, there is the reduction of the line production capacity (make example). The frequency (of such events) depends on the sizing of buffers → for this reason it is important – during the design of the line – to size buffers correctly.

In un-paced lines buffers have to be sized. Two methodologies allow to do it, as they enable to model variability: - analytical approach, based on queuing theory, which requires the formulation of hypotheses (for instance it has to be assumed that the service time follows an exponential distribution) that rarely fit to reality; - simulation, which allows to use various probability distributions and provides more realistic results.

9.1.3 Effect of buffer in a line 9.1.3.1 Example 1 Perfect line balancing (on average) CV of assembly times in station 2

Effect of blocking and starvation -> loss of time due to these phenomena at each station + loss of PC at the end of the line (over a given period). Reasoning on average, PC would be equal to 3600 sec / hour / 60 sec / pz = 60 pz / hour, no loss happens. Thinking on the line dynamics, due to variability and limited buffer size, blocking and starvation may happen and this would lead to losses.

Let’s make a scenario analysis, which of course is an example out of many, that can happen with some probability - Scenario when blocking happens -> sequence of 120 sec at station 2 o Start at WIP = 0 pieces + Limit of Buffer size = 2 pieces; WIP is growing up to reaching the limit; o When WIP reaches the limit, blocking happens: at the end of 5° operation at station 1 (5° cycle), blocking happens -> lost time at station 1; o In the meantime, 3 pieces were exiting the line (every 120 sec). - Scenario when starvation happens -> sequence of 30 sec at station 2 o Start at WIP = 2 pieces (Buffer size limit = 2 pieces); WIP is decreasing up to reaching the limit (0); o When it reaches the limit, starvation happens: at the end of 5° operation at station 2 (5° cycle), starvation happens -> lost time at station 2 o In the meantime, 5 pieces were exiting the line (every 30 sec), instead of 6 as potentials in the period.

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- Overall, there is a lost capacity (1 piece lost if compared to average expected for the period): how many pieces would happen w/o considering the Buffer size limit o -> balanced, make the average over the whole mix o -> balanced but considering the variability and buffer size limit, the two scenarios show that in a given period there is a loss of 1 piece …; this happens as combined effect of blocking and starvation: due to buffer size station 1 was blocked, so we lost opportunity to stock more materials – when upward station was quicker – usable to feed stations in future periods – when the upward was slower –. So, we experienced at the end of the period 1 lost piece out of the line (with respect to the line pace) -> in the short-term period experienced, we would expect 9 pieces exiting, instead 8 exited. o In the long-term period these losses may be avoided (or reduced) if we increase the buffer size (think e.g. of a BS equal to 3, the same scenario would not experience neither blocking nor starvation, so no lost PC).

Station 1 is always generating pieces in its cycle time; the station 2 keeps twice the time of the first station. When the second piece has been elaborated by station 1, we try to enter in station 2, but since the station 2 is already working another piece, the piece has to be placed in the buffer/queue just for a while. It cannot happen if we are dealing with a paced system, because pieces are not leaving the precedence station since the established time occurred. In the buffer situation we should take the average.

The variation of the population is the “coefficient of variance”. On the x axes there is the buffer size, and on the y axes the production capacity.

CV (Coefficient of Variation of the times of the assembly tasks) determines the production capacity (CV = standard deviation / mean)

Higher is the variance of the products I have to produce, bigger the buffer should be, in the constrain of the maximum production capacity (obviously there is a limit) If we have few customisations, we will have low buffer: if we have many customisations or very different each other, we should have big buffers -> if in station 2 I have to do something very different from station 1, I need a big dimension of the buffer. If the variance is low, I will need a small buffer.

Designing unpaced system, one important design question is physically dimensioning the buffer Its design not static, it is “trying to understand how the material is flowing in the line”. There are different methodologies that are used to define the space for the buffer in the unpaced-line.

There are some situations in which we are in the middle, between paced line and unpaced line. ex: Ferrari uses a continuous flow line, which for us is a paced line, since the car is attached to a basement that is moving (the movement is a constrain of the line); but the operator and material can move between the spaces, there is much space between station: this is an element of unpaced line. ➔ Some of this line (paced) are designed to have some square meters free

It is possible to identify a typical behavior of the production capacity of a line as a function of: - the buffer size; - the coefficient of variation (CV = standard deviation of the times required for the assembly tasks / mean of the times required for the assembly tasks). This can be proven by simulation / other methods (even the scenario analysis done was showing that, with increased buffer size, given the variability).

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The figure shows that: 1. Production capacity (PC) increases with the rise of the buffer size (lost capacity is reduced), however the increase of production capacity becomes marginal, less and less relevant. Thus, beyond a certain buffer size, another increase would not significantly impact on the production capacity. There is a trade- off between: o increasing production capacity o increasing the occupied space (and the related costs), the WIP level, the TTP time (flow time). 2. for a given buffer size, production capacity rises with the decrease of the coefficient of variation, in other words it rises with the reduction of the variability of the times required for the assembly tasks compared to their average times. To synthesize, considering all these relevant aspects, it is crucial to find the optimal buffer size.

- Buffer size may have important influence: o buffers enable to limit the reduction of production capacity of the line, due to assembly time variability; o importance of buffers increases with the amount of assembly time variability. - Buffers lead to higher investment/space requirement; therefore, it’s crucial to find the optimal buffer size - The optimal buffer size is influenced by the goodness of assembly line balancing.

First two points are a summary of the previous slide, where the figure showed why buffer size has to be increased to protect from assembly time variability. Third point reminds the effect of ALB on buffer sizing: - In case the line is not balanced, if the Bottleneck is severe (i.e. the time of assembly tasks assigned to the bottleneck is much higher than time of assembly tasks assigned to non-bottlenecks) the buffer sizing is not influent -> all depends on the average behavior of the severe bottleneck, just 1 buffer among station is enough … If the Bottleneck is severe, the probability that the other stations finish before the bottleneck is higher, therefore rarely (if not never) bottleneck station is blocked or starved -> it can work at its full capacity, which determines the PC of the line; - If there is a Bottleneck, but the difference is not severe, of course the buffer become influent, the distribution of buffers along the line may be not equal -> more important are the buffers adjacent to the bottleneck, to avoid that the bottleneck suffers from blocking and starvation, which then affects the PC of the line.

10 DESIGN OF CONTINUOUS FLOW LINES – STATION LENGTH The station length allows to insert a time buffer (i.e. an excess time) to protect the line against assembly time variability, thereby limiting the problems of unfinished pieces. ex: if in a certain period there are some problems with one operator, in order to no stop the line, you should - make the line longer, to give more space and also time to the operator - reduce the speed of the line, because it’s something you can decide ➔ the time is higher, the space is bigger

푉 퐷 = 퐶푇 ∗ 푉 = 푃퐶 where - CT = cycle time - V = conveyor speed (constant) - PC = production capacity

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Design of continuous flow lines - The conveyor moves at constant and really low speed. - When a piece gets in a station (which corresponds to a segment / portion of the line), the operator climbs on the transfer (material handling) platform and, while moving, he / she performs the assembly operations. When he has finished, he steps down the platform and he walks back to the starting point. - Other solutions can be: o the operator may stand and move along the station making the assigned assembly tasks, while the assembly is moving; o in case of small products, he / she may be sit and move slight movements forewords on the line.

Given the conveyor velocity vc, the distance D between two consecutive pieces / assemblies (blocked on their respective bases / on the transfer platform) determines the cycle time: CT = D/vc. To make the distance D (thus being in the same position of precedent piece), the successive piece requires CT, given the conveyor velocity V -> the distance D between two consecutive pieces determines the cycle time: CT = D/V. Having the distance exactly equal to CT*V means that a piece comes out the line each CT.

In case of continuous flow lines, it is necessary to determine three variables: - the conveyor speed: the conveyor velocity has to be chosen: o so as to allow the correct execution of the assembly activities while the piece is being moved; o compatibly with the maximum space available and physical interference problems between operators; If velocity is too high, line length must be high. If velocity is too low, line length, operators don’t have much room to separate each others. o (maximum space available) if velocity is too high, D, and so line length, would be too high (to guarantee the target demand, i.e. CT is given as a constant); o (physical interference problem) if velocity is too low, D would be too low (to guarantee the target demand, i.e. CT is given as a constant), and operators would not have much room to separate each others (i.e. physical intereference) -> would be too closely working. - the stations length; the station length can be a quantity bigger (than) or equal to the distance D, but it can never be smaller than D -> it means giving to operators a time which is at least equal to the cycle time (it cannot be lower … -> no completion would be clearly higher). Then L ≥ D - when L > D, then L > CT * V -> it means the conveyor acts as a (time) buffer -> the operator has some extra time to finish his / her activities, if he / she does not finish by CT. o In continuous flow lines the increase of buffers size (i.e. increase of the stations size) doesn’t imply an increase of the production capacity (as it happens in un-paced lines), in this case the PC is fixed by the conveyor velocity and distance; the extra time protects the line against assembly time variability, limiting the problems of unfinished pieces. o Similarly to un-paced lines, a buffer leads to a tradeoff: it implies the occupation of more space, longer flow times through the line and higher WIP level, against a reduced probability of no completion, so higher actual PC outcome of the line. So there is still the problem of finding the optimal buffer size. (Reading from left to right) Given the flow time, it is possible to determine the station length. Station length should be, at least, equal 퐿 퐷 퐹푇 ≥ 퐶푇 ↔ ≥ ↔ 퐿 ≥ 퐷 where 푉 푉 to the distance between consecutive assemblies. - FT = flow time - CT = cycle time (Reading from right to left) The longer is a station, the more an - V = conveyor speed (constant) operator has a time buffer to complete his / her tasks in the eventuality he may exceed (occasionally) the cycle time. The more is FT, as a time frame (time buffer) within it is possible to conclude.

Defining the station length is equivalent to defining the buffer size: buffers enable to limit the problems of unfinished pieces, thus reducing the impact on the production capacity of the line.

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The longer is a station, the more an operator has a time buffer to complete his tasks in the eventuality he exceeds the cycle time (as it is shown in the figure). This condition pushes to adopt very high station lengths. However, it determines the disadvantage of having high investment costs and space occupancy costs. Furthermore, since increasing stations length, as it is fixed the distance between consecutive assemblies, there are many products being assembled along the line, and so a high WIP (increases the working capital).

To synthesize: - the distance between two consecutive assemblies is related to the cycle time and the production capacity; to modify such a distance means to modify the cycle time, thus the production capacity; - the station length is not related to the production capacity, but it affects the probability of no completion, the overall length of the line (and, so, the investment costs) and the quantity of products WIP which are being assembled along the line; therefore the optimal solution of buffer sizes would be based on cost, considering expected cost related to the unfinished pieces + line cost (including WIP).

Techniques to make the buffer sizing are similar as in the case of unpaced lines. - analytical approach, based on queuing theory, which requires the formulation of hypotheses (for instance it has to be assumed that the service time follows an exponential distribution) that rarely fit to reality; - simulation, which allows to use various probability distributions and provides more realistic results.

The behaviour observed by means of a simulation starts from the Lmin, and measures the prob of no completion (# unfinished pieces/tot at the station(s)) which is reduced as lenght increases (as it could be expected) -> reducing the ECUT but increasing the LC. Remark in case of a Continuous flow line when the operator can stop the line: the number of times this happens is low if L is high; this loss of PC is then low. There is still a trade-off.

L ≥ D -> reduces probability of no completion

In continuous flow lines stations can be all open or closed (but in the same line there could be both closed and open stations in the same line).

10.1.1 Open stations Stations don’t have defined boundaries that separate each other, then the operator can easily cross over them, in order to anticipate begin or to postpone end of his / her assigned operations. In this case, along the line there are areas which are shared by operators who belong to adjacent stations: - an upstream zone, which the operator of the station k shares with the operator of the station k–1; - a downstream zone, which the operator of the station k shares with the operator of the station k+1.

This does not imply, necessarily, that the operator can work concurrently in the shared area/segment as there are still the constraints as precedence relationships amongst operations. Some options that can be found for open stations: - Open stations can be restricted by some constraints in the range of action, as e.g. there are limits for the equipment to be moved far beyond the boundaries. - Open stations can be open downstream, or upstream, or both.

10.1.2 Closed station Operators can’t cross over stations because it is unwanted or sometimes it is impossible. For instance, a closed station is strictly required: - if in the station particular environmental conditions (isolated because of painting operations using spray, heating chambers, … -> example with robots, automated); - Physical interference problems b/w operators of adjacent stations are undesirable. Open stations are suggested when assembly times variability is high. It could help reducing the probability of no completion with lower station lengths (given the assembly times variability).

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11 ASSEMBLY LINE – EXAMPLE

- Product BOM built into the layout Electric switches (some how more complex, so complexity is broken down in many stations, making subassemblies …) - Unpaced line (lenght of the handling system … queuing in front of the assembly machines) o The lenght is enough to manage small / frequent problems (blockages) o Layout occupation (due to the lenght) is motivated by reduction of PC losses

11.1.1 Bottling line Automated bottling line (a number of operations: filling bottles with the liquid + packaging etc.) Continuous flow line - when they are filled with liquid, bottles need a lot of time; at the same time the requested PC is high, so the CT is very low; - how to cope with this challenge? (focus on filling operatoon) Parallelizzation -> while filling is working at the same time different bottles are plugged in different working positions and moved-> the station has a lenght / has a rotational speed / enough to enable the long time for the filling operating cycle -> but every filling cycle top k bottles exit -> top/k is what is needed (respecting the low CT) - Note that the bottles are fixed and so we can avoid problems of liquid leakage, etc.

Integrated concepts of lines to the industry. This is a competitive alternative to traditional lines that adds value to the complete packaging line. - Suitable for all liquids packaged in PET, our Combi systems combine blow moulding, filling and capping in a single integrated system; - This eliminates conveying, empty bottle handling, accumulation and storage, line layout with a smaller footprint, -> integrated system (fabricating the PET)

12 AUTOMATED ASSEMBLY Automated assembly is performed by using assembly lines, assembly robotized workstations and assembly cells. It must be taken into account that the current technology does not allow to perform assembly operations in which complicated handling or visual inspection is required, at competitive cost-benefit conditions.

On the contrary, when the assembly process is well defined and standardized and the product volume is high, automated assembly lines are used by many years (e.g. assembly of single-use syringe, ballpoint pens, ...). High speed, mainly mechanical based lines, are used in these situations. Here, an important aspect to be considered is the implementation of design for assembly methodologies in the product development phase because this can greatly simplify the design of the assembly system equipment.

Automated assembly cells are flexible assembly systems based on the concept of the automated assembly of a family of similar products, taking into account the possibility to perform the same types of operations and to use the same types of fixtures, tools (e.g. robot grippers) and components for the given family of products.

However, due to current automated technology limitations, the similarity of products must be high so to be possible to realize cost effective assembly cells.

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Simple robotized arm Robot classification by movement type (pick and place) - Kinematic structure - Work envelope

Body, shoulders and arms, up to the hand where it is fixed the tool / fixtures required to make the operation (e.g. welding) - Joint can be a revolute or prismatic - Revolute joints provide single-axis rotation function - Prismatic joints provide a linear sliding movement function (between two bodies)

Programmable robot - Cartesian coordinates system -> Cartesian coordinates robots -> XYZ robots (3 mutually perpendicular axis) - Cylindrical system - Spherical system

Objective: to position and orient the end effector

Circular machines are made by a rotating table on which the product assembly is put; transfer of product from the various assembly stations in a synchronous way is performed. One or two stations are dedicated to product input / output to/from the assembly machine. Solution is used for small products. Cycle time is very short (in the range from 0,5 to 2-3 seconds).

Linear machines are made by a roller transfer line on which pallets move in asynchronous way by friction rollers. Assembly stations are placed along the transfer line. Pallet is blocked by suitable equipment when it enters a station. Buffers can be provided among stations. Pallets can wait in buffers thank to slip by friction rollers. Solution is used for small products, when many stations are required. Cycle time is short (in the range from 1 to 5 seconds typically)

Today we can have automotive assembly system; they can produce small pieces; components are pledged together station by station, there are robot or dedicated machine which are executing the assembly of component. Our activities of assembly normally for a single product are executed by robots and dedicated machines; the design of this kind of system can be done with the method we have studied The typical assembly line of an engine: it is a product produced in a plant, in that “engine line” there are more than 150 station, starting from raw material (transfer line), then it is becoming an assembly line. In the same line we have both operator and automatic machines. There are all the elements of an industrial technologies.

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13 QUESTIONS FOR REVISION The following questions are concerned with the main contents of this lesson. They should help you to revise for examinations: - Be aware of the procedure for dimensioning and balancing assembly lines. - For which kinds of products are the different assembly layouts used? Think of some examples. - How do you determine the assembly time of operations using the time study and the MTM methodologies? - How can you plan the assembly shop for a target volume of production?

14 REFERENCES - Garetti, M., Design of production systems, FrancoAngeli, Milano, 2015 - Garetti, M., Lezioni di progettazione degli impianti industriali. CUSL, 2010 - Reid, R. D.; Sanders, N. R., Operations Management. 2nd edition, Wiley, 2005 - Slack, N.; Chambers, S.; Johnston, R., Operations Management. 4th edition, Pearson Education, 2003

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1 INTEGRATED DESIGN PROCESS Module of production system, which uses different module for running some part of the design of production, using modelling technique for several reasons.

Normally, industrial or manufacturing companies have few processes: designing and production one; this picture is saying that production companies start from a designing point of view: how many design processes they have? We called them integrated designing processes.

- Vertical process: most of the companies have to design a product, collecting the requirement, design, engineering the product etc.; then, from a point of view of a product/design process, there are person who design the product and producing the product, and in the rest of the company somebody is providing services. This is the so-called “product lifecycle perspective”, which is the vertical part of this image. - Horizontal process: process in which we have designer engineer, who are in charge of the design of the production system, to decide for example which are the requirements, what should the system produce, the manufacturing capabilities and the facilities, person needed to produce… In the real life of companies, the horizontal and vertical processes are happening in parallel way, at the same time in which the product designers are still finishing to design the products, somebody is already starting to design the production system ex: typical example of the car industry, when they create a new product, a new car, product designers are trying to finalize the design of the different component, and engineer and designer starting to design the production system in which the car will be produced. This is the only way for being fast: today the market is asking to build the car in a time to market of 18-20 months, there is no time to divide the process, there is no time to have a year of product design and a year for the development of the production system, everything should happen as much as possible in the same period In the picture we can see that there are two main parallel designing processes inside the companies; the picture is telling us that today many tolls, technologies and software for designing have been invented and can be adopted. In Industry 4.0 revolution, companies can use many digital designing tools to design production system (ex: some of the tolls are CAM, CAD...). Today, in particular in big companies, the processes of designing process and designing system are happening together using a comprehensive use of tolls. Till today we have seen the analytical model, in the next month we will deal with some of these tolls: we will use MATLAB for the production process simulation, that is one of the tolls used in this contest. Everything that we did is related to the horizontal process and is based on the data/information/results that are coming from the vertical process.

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LAYOUT OF A PRODUCTION PLANT A production system is organized as a kind of map: this map is a layout; when we talk about the layout of a plan, it means that we are physically dealing with the factory and it shows how the different machines (department, lines, job shop) are physically installed in that plant. From one side the layout is very physical (why am I putting there a machine instead of the others) and from the other side is also a logical activity.

ex: in this map we see a representation of the layout of an Italian Owo company, in which there are different job shops and the arrows are Voltapile Officina Area prepazaione fustelle telling us the flow (material flow) of the production system. This Taglio Piegatrici PF Finestr. production system seems to be a mess, a typical job shop with a list Stampa Stampa UV Fustelle MP of machines with several arrows mixed. Staccatura Piega This picture is a specific method invented in the 60’s, it is a method incolla used to help designer in charge of designing a production system to identify the most logical layout.

FACTORY PLANNING MODEL FRAMEWORK We are focusing our attention in three main parts since we have the factory which has to be planned or designed: Capacity planning: this is what we have done in Job Shop, Manufacturing cells and transfer line; we have dealt with NH (job time), cycle time (lines), pieces per hours, but behind there is always the concept of capacity; capacity means being able to produce at a certain speed, that is different to capability, which means what you are able to do, while capacity means how much you are able to do; we have always discussed/solved exercises dealing with capacity. Material flow: the production system is a dynamic system in which we have pieces flowing, so we should consider how material is moved; the material flow has been already been defined by us, and it is part of the definition of the different archetypes: job shop, manufacturing cells and transfer line have three different type of archetype from a material flow point of view; in particular, in the manufacturing cells we had use the ROC (Rank ordering cluster technique) which is part of a group of method, called the production flow analysis. Everything that we have done till today was done at a logical point of view, we were never asked to put material in the plant; also in the assembly line we have dealt with a logical perspective Now, we are moving from the logical to the physical perspective, we are trying to put our machines in the production system: this is called layout design. The previous picture with the mixed arrows is showing that layout design is important as well as job shop design and production flow analysis; it was a typical result of a company that has missed the last step: they do not consider properly the layout and they put one big department in the wrong position, causing big problem in this case in the material handling In the cases that we did there was often not just one solution: in the designing phase there could be more than one solution having sense from the engineering point of view; the design engineers are looking for different solutions and they should find the “best one” among them.

In designing the production system, we have many perspective: capacity, material flow and factory design; and in considering that we can use different models, technique, methods, algorithm. ex: when we design a typical Job Shop from a capacity point of view, we have done the “rough calculation of Needed hours and available hours and the analysis of workload”, considering a deterministic (well-known) and stationary (that is working in a specific way) production system. It is different when we have used the “line balancing”: we were adding more knwledge from a deterministic to a statistic knowledge using the probability of no complention Now we will deal with simulation, moving to another level of knowledge: we are not only forecasting a static result, but also dynamic; the simulation can run a system that is continuously changing.

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2 FACTORY LAYOUT PLANNING (FLP) ; FLP consists in the definition of the physical organization of the factory; it a physical decision linked to the position of machines, department, lines and so on. We are deciding how to design the map of the production system. - FLP concerns the search of the most efficient location of the shops (areas of activities) within a given building or area available in a building - Shops might have needs of space very different one from the other - The objective is the minimization of costs of «relation» between the shops, respecting plant constraints (facility physical structural constraints, building constraints, floor maximum load allowed, service infrastructures); We should design the layout of the production system to avoid waste and other problems.

➔ Results of FLP: CAD drawing of the factory layout These activities, today, is mostly supported by computers, instead of paper -> CAD system

General layout, with identification of location of each shop.

The drawing of the detailed layout in which the following elements are identified: exact position of the shops, structure of corridors/passages, exit and entry points, position of machine and workstations within the shops

We should know that this activity of layout planning is normally happening step by step, level of detail by level of detail: we can take decision about a group of activities, then we need a layout at a very detailed level, used by the worker to install the machines, for example.; starting from decision of a general level and then we do the so called “detail design” When we have to design a line, we have to take decision on where to put it, how to partitioning it and how every single station should be; this design is done step by step, and could happen in a long period of time, during the years, months by months.

OBJECTIVES OF THE FLP PROBLEM One of the traditional objective is to optimize the efficiency of material flows and the relation between productive areas (and non-productive areas). The main things that should be considered is the production flow, the expected amount of material that should be moved from one department to the others is the basic element that should be optimized (technical element) ex: reducing the number of transfers; from an economical point of view, I can evaluate the transportation as costs, it depends of how we transport the materials (human resources, robots, machines, handling system …) To find the good layout, we should start with the identification of the production flow and find which is the way that costs less, it is a way to minimize/optimize the cost of layout; a good layout should be a solution that minimize or reduce the costs of production flow

The FLP problem is multi-objective! The last part of the formula means that not only the movement should be considered, we should consider some other relationship that can happen

Objective Function: - fi,j = material flow between two areas/shops i,j - ci,j = cost per unit of movements between two areas/shops i,j - di,j = distance between two areas/shops i,j

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MODELS FOR FLP ANALYSIS Formulate the problem as objective functions with given constraints (linear programming models). We have already done all the capacity design and we know how machines could stay in a certain amount of space; now we have to display the production areas, to design and dispose the machine in the best logical way, looking at the square meters needed to install them

Objective function 푚푖푛 ∑푖 ∑푗(푓푖푗 ∗ 푐푖푗) ∗ 푑푖푗

We use average distances, calculating how many meters in average we are crossing to go from one area to the other one; but the distance can be different! We are dealing with boxes, so it is difficult to estimate only one way to define the distances NB: we are looking at movement in terms of distances, here we are not considering the corridors

There are normally three different way of doing; no one is perfect, they are hypothesis of what could happen - Rectilinear distance: we are taking the middle/centroid of a production areas and looking at the distance in a linear way - Euclidean distance: average one based on the centre - Actual distance: when we had designed the corridors, we can have the real measure of the distance; it is the perfect model of moving the system

Nowadays, we can use these methods in a CAD system: I can tell which are the corridors, or which are the starting point, and make the calculation about the distances in different ways

2.2.1 Formulate the problem as objective functions with given constraints (linear programming models) Example using an analytical model giving us an optimal solution in terms of linear programming model considering the costs - xi, yi = coordinate of barycentre of the shop i Constraints (Example) - L, W = geometric dimensions of the building 퐼푖 ≤ 푥푖 ≤ 퐿 − 퐼푖 - li and wi = geometric dimensions of shop i 푚푖푛 ∑ ∑(푓 ∗ 푐 ) ∗ 푑 푤푖 ≤ 푦푖 ≤ 푊 − 푤푖 푖푗 푖푗 푖푗 - ubi and lbi = max geometric dimension of shop i 퐼푏 ≤ 2퐼 ≤ 푢푏 푖 푗 푖 푖 푖 (orientation of the shop) 퐼푏푖 ≤ 2w푖 ≤ 푢푏푖 … - ...

FLP METHODOLOGY: PHASES OF THE PROJECT Systematic Layout Planning Methodology (Richard Muther)

The linear programming model has to be solved, giving some constrains. We will see something heuristic more linked to the real practise There are a list of steps or activities happening, that the person in charge is trying to follow; we are using this schema to understand the activities

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Analysis, we have to know the type of products, we should understand the material flows, which material should be moved from one department to the other, and also the relationships, between production facility and operator, or between one facility and another, or between a material and an operator ex: - a department has to be supervised by the same person - the setup has to be done by the same group of experts - a machine needs to be very close to the power generation area - the coffee machine should be put near the area in which the person work, not the robots - workers need to have toilette and service, so we will put the production area, in which more worker has to stay, next to the services NB: we are talking about machines and people etc, not about material, because it is related to the material flow I should know these relationships before, in advance, we should not discover these information later

When we have this data collected, we can start the design, starting from the building of the graph, creating a first sketch/graph of the layout (now with the high level of detailed, it should be increase step by step), let’s see how it will be, in a very general way, in terms of area and their connection; it should be a graph in terms of logical spaces, and at a certain level we should consider also the space diagram, considering the square meters; in doing this activity step by step, we can evaluate, take decision, discard some options and take the other, the graph could change after some evaluations and decisions

When we have this preliminary representation, adding some elements about costs or movement, we can arrive at a final solution; to arrive to some final solution, we can use some different methods: heuristic method used in the last stage of this diagram, or other methods which use data NB: this is not the only way of doing, but this it’s done step by step, it’s more logical

After that, we can move to the last step, in order to generate some alternatives, through different possible methods; each archetype of production type has its own advantages or disadvantages, and its specific way of doing -> we are doing a layout design ex: if we have to produce many products of the same type, we are going to use a line; if we have many products with a reduced number of pieces, we can use the Job Shop

NB: the layout design is not really the last step, is not the final phase; design process is always iterative: designers are starting from a rough idea, understanding which are the areas, understanding whether it makes sense to use a Job Shop or other archetypes, and step by step enter in the calculation and go back. The elements seen so far (the production archetype and layouts) are not made in a specific order, but they have always connected each other; it is a matter of how the company is approaching the production

PRODUCT ANALYSIS First activity that a company has to do is going back to the demand, the volumes that the company has to produce, based on that all the other elements are performed. The company should have understanding of their products ABC analysis on products supports strategic definition of factory layout -> layout product oriented vs. layout process oriented The result depends on the type of products, some products are more important for the company, so I should dedicate an area for them

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MATERIAL FLOW ANALYSIS The flow diagram allows to identify the requirements for movement between shops -> from technology diagram (families of) of products to origin/destination matrix of flows This table is normally called from-to chart; it’s a very useful way to explain the material flow

NB: column and rows are always the same, they represent the production areas There is a flow between one area to another: the numbers inside the table can represent the number of pieces in different period of time (one minute, one hour, one day…) or also the amount of cost The table is always the same, the number inside can be used according to different units. fij * cij fij * PRODUCT AND MATERIAL FLOW ANALYSIS pij Example for high volumes products fij The production system is a flow and material are moving according a certain process, but it is a process in which we have resources that can be kind of bottleneck (ex: in the design lines) We were imagining what is happening in the real life of industry: we have a production flow in which machines and resources are interacting with the production flow; some of them could become bottleneck; we should understand how to manage it, leaving a buffer before (leaving square meters) or changing the cycle time

Ideally, the flows have always the same movements, the same flow, without any stops; in the exercise we have seen that is not so easy; in the layout design we should consider that the layout is something in which we have the resources and material flowing in a dynamic way; this dynamic part is linked to something that is flowing, we should go step by step and look at how the different activities are finding space

GRAPH AND SPACE DIAGRAM Each of these circles is one of the production areas, the lines represent the connections needed between them. The first is the graph method, the second is the space diagram, which is our result: we should arrive at the solution with dedicated areas which are occupying certain spaces, in terms of square meters The space diagram should also consider physical constrains: buildings, plan…

ex: the spaces are occupying rectangles, since buildings/plants are built in rectangles Normally we should move step by step from a graph diagram method to a space diagram method; this is telling us how many square meters are left for production area number 9 or how many square meters are left for buffer number 10, and so on.

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FACTORY LAYOUT DRAWING This activity can be supported by some design tools which are guiding us in a certain way; when we have the square meters from each area, we can use a CAD system Example of CAD factory layout with identification of shops with high density of flows; in this case, we can use the different colours in order to visualize the production flow The two pictures are quite different, because the designer can move the areas and have directly the result of how the material will be moved: this is an example of factory layout moving/growth supported by CAD Tip: shops with high density of flows should have put one close to the other

FLP METHODOLOGY: RELATIONSHIP ANALYSIS For deciding how to position materials in a plant we have to consider the relationship ex: we should consider that the services should be close to the place in which operators are working

Since the 60’s there was the method of “Relationship Chart” identify the requirements of «relation» between shops (areas of activity) (between shop i and shop j) -> causes and importance of relations are identified by dedicated codes

We have all the areas, shops and the intersections; the relationships are described in terms of the level of importance or reasons - The scale gives us the relevance: 100 is the highest reference. - The code is telling the reason: 1 = supervision. ➔ Somebody in A has to supervise B This scale is not a standardizing, it is a way of doing, a way to identify the relationship and also a way to express a model; this table as starting point (ex: the CEO’s office should be close to the one of the secretaries)

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3 FLOW ANALYSIS VS RELATIONSHIP ANALYSIS Graph and space diagram (based on the material flow analysis) are put together with the relationship chart

These three elements are the main tools needed and used to a FLP planning - Form/to chart - Graph diagram - Relationship chart These tools are used till this point, now we can make some analysis combination, alternatives using these information

4 METHODS AND CRITERIA FOR FLP PLANNING Many tools and method have been invented to try to provide a solution to the previous formula; this formula is telling us that we are optimizing the costs and optimizing the relationship, in which alpha is a weight and r is representing the relationship; this formula is telling us that I want to build something in which I do not have troubles between the different resources and areas During the years have been invented optimal or heuristic method for guiding and supporting designers in the layout; we are going to use three method: the first is very simple, the other two are more complex.

HEURISTIC TECHNIQUES FOR THE SOLUTION SEARCH We use three methods: MAT, CRAFT and ALDEP; we cannot expect that these methods are giving an optimal solution, but they will give a good solution (close to an optimal solution); all these methods are based on an algorithmic approach. Software’s tolls as MATLAB have already these elements implemented.

- Search of a «good» solution - Automation of the search vs. interactive search

In computer science, artificial intelligence, and mathematical optimization, a heuristic is a technique designed for solving a problem more quickly when classic methods are too slow, or for finding an approximate solution when classic methods fail to find any exact solution. This is achieved by trading optimality, completeness, accuracy, or precision for speed. In a way, it can be considered a shortcut. The objective of a heuristic is to produce a solution in a reasonable time frame that is good enough for solving the problem at hand. This solution may not be the best of all the actual solutions to this problem, or it may simply approximate the exact solution. But it is still valuable because finding it does not require a prohibitively long time. Heuristics may produce results by themselves, or they may be used in conjunction with optimization algorithms to improve their efficiency (e.g., they may be used to generate good seed values). (Wikipedia definition)

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4.1.1 Heuristic MAT (Modular Allocation Technique) – starting from green field The plant at the beginning is empty (green) and we have to dispose the things in the system (layout), trying to minimize the movement costs;

- Input data: o the layout, defined at a logical point of view and in terms of areas o two different types of warehouses, one for raw materials and one for finished goods, in the layout that has still to be created; the idea is to distribute these in 4 departments -> POS 1,2,3,4 - Other data: weight of relationship between shops -> from-to table o the shops are reproduced both in rows and in column (WH, R1, R2…) o the numbers inside represents the relevance and the functionality of the connection ex: we have to move 275 pieces of raw material from the raw materials warehouse to R1

They are ordered according to their weight (ex: WH raw-R1 have a flow of 275, while R1-R2 has a flow of 225) Based on this we should be guided to position the department in the areas - Order couple of positions with growing distance to minimize the total cost of movement - Order of couple of shops with decreasing flow to decrease the dimension of the stock moved, so to reduce the costs

Design criteria: shops with larger exchanged flow should be positioned one beside the other (to minimize operative costs)

In the table, we have four areas - R1 should be position at first since it has a great connection with the WH - Then we should position R2; R2 can be very close to R1 or in another department in contact with R1; from a logical point of view,

R2 can be positioned in two different areas

We should be inspired by some archetypes to find the best solution: it could be positioned in a U-shaped or in a linear position

This is not telling us the optimal design solution; the method is telling only step by step which is the next product to be positioned; we should prefer one to the other according to our point of view (in this case the U-shaped)

Working with an algorithm means to follow the steps given, but the results sometimes are interesting and useful, but sometimes they are not; algorithm need to be used and then we have to take decisions, it doesn’t show the final solution

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COMPUTERIZED LAYOUT TECHNIQUE (ALWAYS HEURISTIC METHOD) Suppose that we are given some space for some departments. How shall we arrange the departments within the given space? We shall assume that the given space is rectangular shaped, and every department is either rectangular shaped or composed of rectangular pieces. We shall discuss: - a layout improvement procedure, CRAFT, that attempts to find a better layout by pair-wise interchanges when a layout is given and - a layout construction procedure, ALDEP, that constructs a layout when there is no layout given.

4.2.1 Heuristic CRAFT (Computerized Relative Allocation of Facilities Technique) - Starting with an existing layout - Matrix to exchange position of shops - Evaluation of cost of the exchange of position (difference of objective function)

CRAFT is one of the first heuristic models (Computerised Relative Allocation of Facilities Technique) It is based on the minimization of moving cost among the departments, between the different areas It needs a starting layout, as an input to be executed; it is considering also some other elements, facilities

4.2.1.1 Input - Initial Layout - From-to table - Cost of the movements - Number of departments to be allocated and their constrains (we are not considering constrains in our exercise) ex: we have a typical rectangular shaped with 4 departments/shop A, B, C, D and we know the distances between them (calculated according to the positioning) and their lengths

- considering as position its centre on the graph, where the department A is? - and what is its distance from the department B?

Centroid-based distances 푑퐴퐵 = |푥퐴, 푥퐵| + |푦퐴, 푦퐵| = |25 − 65| = 40 Euclidean and rectangular way to define the positions and to do this we need to have the position of centroids - The first chart is saying the trip per day ex: every day we have 3 trips between the departments A and B (2 from A to B and 1 from B to A) - The second table shows the distance between the two departments; obviously is symmetric

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This kind of tables translate the movement in costs: usually the first one is given in €/meters, the second one shows the total cost for each from-to movement

ex: from A to B we have a total cost of 80€ from A we have a total cost of 400€ = 80퐵 + 100퐶 + 220퐷

- Given a layout, CRAFT first finds the total distance traveled as illustrated on the previous slides - CRAFT then attempts to improve the layout by pair-wise interchanges o If some interchange results some savings in the total distance traveled, the interchange that saves the most (total distance traveled) is selected o While searching for the most savings, exact savings are not computed. At the search stage, savings are computed assuming when departments are interchanged, centroids are interchanged too. This assumption does not give the exact savings, but approximate savings only - Interchanges can be done on 1 way, with departments of that are next to themselves (one side at least should be connected) We start from one area and we can try to change this one with another; the movements are based on a starting point: our starting point gives a cost of 1020€

Let’s change A with B, and do again all the calculations Estimated cost reduction may not be obtained after interchange; in this case, this exchange doesn’t make any sense, because the total cost is higher than the first solution

Possible exchanges New total layout cost In this table we have a list of alternatives, with the related total cost of in the initial layout each solution: we can see that there are many changes; for each A with B 1.060 change, we recalculated the total layout costs. A with C 955

A with D 1.095 We change A with C having a cost of 955€ This is not possible, B with C since B is not next to C B with C cannot be changed since they do not have a connecting point; in the original layout according to CRAFT’s constrain, we are changing only rectangles with at B with D 945 least one connecting point. C with D 1.040 B with D and C with D have been calculated

In terms of money the best solution seems to be changing B with D; if we implement physical it has this aspect in the right NB: we should always respect the square meters

In this figure, we should look at the detailed level of machine, because CRAFT is not taking care of the type of machines of each departments, it is just making calculation changing in order to find the minimum cost An improvement procedure, not a construction procedure; this technology is useful to evaluate different alternatives, to provide more solutions

Sometimes, an interchange may result in a peculiar shape of a department; a shape that is composed of some rectangular pieces; we have executed CRAFT using the typical centroid; when it has rectangular shape, it is easy to find, but in this case, what is the centroid of D? We can measure it analytically.

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4.2.2 ALDEP - Automated Layout Design Program While CRAFT is an improvement procedure, ALDEP is a construction/building procedure CRAFT requires an initial layout, which is improved by CRAFT; ALDEP does not need any initial layout, it constructs a layout when there is none

ALDEP constructs a layout given: - Size of the facility - The departments/shops - Size of the departments/shops - Proximity relationships (activity relationship chart, production flow relationship or other type of relationship) - A sweep width (defined later) From these data, ALDEP start with a simple assumption of physical representation, with an initial grid of our facilities, and let’s decomposed the area in terms of squares/rectangles

- The size of the facility and the size of the - The departments and the required number of departments are expressed in terms of blocks. blocks are: - The procedure will be explained with an o Production area 14 blocks example. Suppose that the facility is 8 blocks o Office rooms 10 (horizontal) x 6 block (vertical). o Storage area 8 o Dock area 8 o Locker room 4 o Tool room 4

4.2.2.1 Example ALDEP is based also on the relationship graph, in which we have different areas and we have information about each of them; in this case this show the necessary of each relation between department, expressed through letter (American way of doing) A: absolutely necessary E: especially important I: important O: ordinarily important U: unimportant X: undesirable

ALDEP starts to allocate the departments from the upper left corner of the facility. The first department is chosen at random. By starting with a different department, ALDEP can find a different layout for the same problem.

Let’s start with dock rooms (D). On the upper left corner 8 blocks must be allocated for the dock area. The sweep width defines the width in number of blocks. Let sweep width = 2. Then, dock area will be allocated 2 x 4 = 8 blocks.

To find the next department to allocate, find the department that has the highest proximity rating with the dock area. We notice from the relationship chart that D has a relation A with Storage, U with Loacker Room, O with Tool Room, O with Office Room and I with production area: storage area (S) has the highest proximity rating A with the dock area; so, the storage area will be allocated next. The storage area also needs 8 blocks. There are only 2x2 = 4 blocks, remaining below dock area (D). After allocating 4 blocks, the down wall is hit after which further allocation will be made on the adjacent 2 (=sweep width) columns and moving upwards.

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See carefully that the allocation started from the upper left corner and started to move downward with a width of 2 (=sweep width) blocks. After the down wall is hit, the allocation continues on the adjacent 2 (=sweep width) columns on the right side and starts moving up. This zig-zag pattern will continue. Next time, when the top wall will be hit, the allocation will continue on the adjacent 2 (=sweep width) columns on the right side and starts moving down.

NB: ALDEP start with a department randomly chose; the limit of ALDEP is that if you start with a different random department, you can obtain different solutions, there are many alternatives You can use ALDEP to create, and then easily using CRAFT to calculate distances and costs; in real life, there are some computers proposing different alternatives, and other that find the good solution

5 COMPUTER-ASSISTED LAYOUT USING CAD

Centroid based distances Corridors-based distances

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09. Introduction to Process Plants

1 CLASSIFICATION OF PRODUCTION SYSTEM We have the division between manufacturing plants and process plants, and we have done the parts production and the assembly. In the left branch (process plants) we have primary or process oriented industry: the process industry physically produced chemical, textile, pharmaceutical, it is producing “primary material”, and this will be the input to the manufacturing industry. Process industry has physical plants and somebody should be able to design them, such as a pharmaceutical plant: if you are the designer or engineer involved in the design of a chemical plant, you should have by your side the chemical engineers experts. By law a production plant of the process industry should be managed by a person involved in that type of industry; this type of industries should be designed and managed from a chemical engineer, because in the past there were problem related to pollution. In Italy there is the “Normativa Seveso”, because of what happened in 70’s in Seveso.

We are designing a process plants for delivering a continuous flow production or for producing batches of production, on a batch-based design. All the processes industries are designed according to these types.

2 PROCESS PLANTS – GENERAL FEATURES A process plant is physically formed by a series of production equipment used to make non reversible chemical- physical transformation of materials through a fixed technological routing.

Nowadays the processes are so big because we are dealing with production systems which produce raw material, so they have to produce high volumes at a very cheap costs -> we should have processes which able us to reach the economies of scale of that type of plant; a design engineer should look mainly at this, how to reach the economies of scale

They are a lot of pipeline, because process industries start from some raw material and transform them through some physical and chemical transformation, for which it’s necessary, in order to have a continuous production, to build a long pipelines structure, according to the safety concepts and rules

Plants are designed to operate: - a continuous flow production process - a batch production process.

Products, processes and product routings A process plant consists of a (group) series of production equipment. The driver that guides their selection in this case is the Industrial Technology in terms of technological processes and parameters required to achieve finished products. Whenever the technology has been decided, many decisions are closely subsequent and, in particular, the technological routing is fixed / obliged.

The production equipment included along this kind of plant are making non reversible chemical-physical transformations: this non-reversibility cannot allow at the end of the whole process to easily identify component materials into their products; in other words, material transformations have been so relevant that are non- reversible > materials changed their nature due to such transformations (e.g. limestone/marl to clinker to cement). This issue is quite common to all plants in the process industries: their products are result of non- reversible transformation. These sectors are: Petrochemical / oil refineries; Cement, glass, rubber, paper production; Chemical production; Pharmaceuticals; Foodstuffs (sugar, flour, etc.); Gasses (Oxygen, nitrogen, hydrogen, etc.); Plastics (PET, nylon, etc.); Metals (steel, aluminium); Agricultural (fertilisers, etc.) …

Products of process industries are used in many types of secondary industries (secondary processes / manufacturing): they are raw materials for further manufacturing applications. Often, products are considered commodities, even if some companies try to brand to gain differentiation. Of course, this brand can be built upon

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particular products possible thanks to some technological capabilities; on the other hand, the product variety is clearly limited respect to the discrete manufacturing.

(Looking now at how transformations can be realized in a process plant) we have two options: materials subject to transformations are moved continuously through the production equipment of the plant (continuous flow) or they are processed as batches, this means that each production equipment is intermittently changing batches (of different products) and moreover storage silos / tanks are considered where batches are waiting for the next operations (discontinuous transformation thanks to storages). Overall, the production flow is realizing a continuous or discontinuous transformation respectively with absence or presence of inter-operational buffers / storages.

Remember that somehow parts of the production process, it is inherent to deal with impurities / wastes which are reused as much as possible or removed to reduce environmental impact (e.g. air pollution … ).

The production flow is serial, analytical or synthetic. Continuous transformation (with different products) -> oil, plastic, gasses: from a single raw material, through different transformations, we arrive at the end with different final products

Discontinuous transformation -> it could be for example pharmaceutical industry: we have some different basic ingredients; through the chemical industry they are transformed and them combined into a single final product

Different characteristics of production flow are observable in process plants. Considering continuous / discontinuous transformation: - raw materials are converted to finished products through a series of production stages through which the material is continuously flowing (i.e. continuous transformation > e.g. nylon, continuous flow process); - semi-finished/intermediate products are stored within the process (depending from technology, this can be possible and also needed) > this is done thanks to storages b/w different transformations, and storages may have also a function relevant for technological transformation (not just as stock holding point, but also for technological transformation leading, e.g. cement process, to mixing the load of materials in order to obtain homogeneous characteristics for next phases > e.g. after the grinding process takes place in a raw mill to reduce the particle size of the raw material, the output of the grinding process – called ‘raw meal’ – is transferred to a homogenization silo before the clinker manufacturing process; before the grinding process, there is a pre-blending storage where materials loaded at different times in the storage are blended before entering the grinding process) > (discontinuous transformation > batch process as in cement, nylon production processes).

Considering analytical/synthetic (from one material to many products or from more materials to one product) or serial (simple transformation of raw material to product):

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- raw materials and semi-finished/intermediate products may be split to provide more specialized processing and finished products (crude oil -> processing and refining crude oil to obtain different refinery products -> see the web site of some producers http://pascagoula.chevron.com/home/abouttherefinery/whatwedo/processingandrefining.aspx); - raw materials and semi-finished products may be joined/mixed to create the finished products (cement from a mix of limestone, malt and other materials; nylon, from a mix of components which derive from petroleum); - raw materials are transformed serially (papermaking > paper is mostly obtained starting from vegetable fibres such as wood pulp and transforming it).

Process plants are highly automated: - relevance of technological parameters of the production process (temperatures, pressures, …); - significant investment in sensors, equipment control, etc.; - control often automated with supervisory intervention.

Process industries, compared for example with manufacturing systems, need less persons, because nowadays it’s really automated: there are some dozens of people, while in a manufacturing plant we have at least hundreds of people per square meters. Automation was introduced for achieving the economy of scale, so the process is mostly done by robots/machines, not by people; this is becoming possible because the technological development At the same time, we have other kind of job for people, because these processes need a lot of control activities and we have also to do the maintenance of the machines; nowadays there are a lot of operators which controls the production system through some screens, thanks to sensors

(To achieve the transformations) keeping the optimal / standard conditions of certain technological parameters is a critical issue of these types of plants; in other words, variations in process conditions are critical and should be mitigated in order to maintain as stable as possible quality and efficiency of the production, as well as safe production. Variations in many variables (materials, process itself, environment) are naturally occurring, leading to challenges in the process control problem, because these are occurring also in real time. In this regard, it is worth mentioning that there are control architectures developed in process plants normally having different layers in a hierarchy from sensors / actuators (lower level) to digital control on field (ex. pump, valve control, equipment control in general) to supervisory control – both automated or semi-automated – at upper level of the hierarchy.

An example of supervisory control is tangible in control rooms, see the case of the refinery http://pascagoula.chevron.com/home/abouttherefinery/whatwedo/processingandrefining.aspx.

Comment shortly the scheme, as logical scheme which can then be implemented in the control architecture.

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EXAMPLES

2.1.1 Example 1 Block Flow Diagram for the production process of Ethylene Oxide

These systems usually be designed starting from the production process and the production flow This draw is a very simplified schema of a production system; each area represents the different transformations, inside the pipes which link the areas we have the products passing through.

(Short intro) Ethylene oxide is a product used industrially for making many consumer products as well as non- consumer chemicals and intermediates; it is important or critical to the production of detergents, thickeners, solvents, plastics, and various organic chemicals…. ; it is industrially produced by direct oxidation of ethylene (in the presence of a catalyst). - The process is schemed out as a Block Flow Diagram. A BFD is a simplified representation of the main phases of a production process through the equipment used to carry out the correspondent operations (only critical equipment for the process are drawn in a BFD, not other components which will be included in more detailed schemes, such as e.g. storage tanks, valves, heat exchangers, … all functional components for the operations); subsequent the flows are represented by directed arrows, normally having the flows from left to right, expect for the recirculating flows >>> on the whole, this results in drawing a fixed technological routing through the sequence of visited equipment realizing the different phases of the production process. - The BFD is an initial representation based on the principle of material flow conservation (mass balances), and it is depicting the production flows that the production system should be capable to produce, both primary flows, any intermediate flows and scraps / re-entrants or reworks (said in general terms). This is, at least, the overall macro-perspective of what is actually occurring within each operation along the production process. - Indeed, from a micro-perspective of the plant/process, some chemical reaction correspondingly happens within the reactor, both desired/main and undesired/side reactions; this leads to the production flows within the BFD. - More precisely, note that the relationship 2:1 b/w ethylene and oxygen flows (40000: 20000 kg/hr) is correspondent to what formulated in the main chemical reaction: if this reaction just happens (one molecule of ethylene and a half oxygen are needed in order to obtain ethylene oxide, C2H40, which is the desired outcome), we would have just ethylene and oxygen flows (40000: 20000 kg/hr) as inputs and outputs. But undesired reactions occur, resulting in CO2 and H2O; all in all, we have an expected outcome at the end of the reactions, considering both undesired reactions and also the fact that the conversion of the desired reaction is not 100%, i.e. not all the ethylene and oxygen are reacting. - For this process characteristics, some further operations are then required within the technological routing: after the vapor-liquid separation and the subsequent distillation in two sub-phases (subsequent equipment, distillation tower), we obtain the final product (C2H4O) + the elimination of all side products (CO2, O2, H2O) + the recirculation of raw material ethylene (previously not reacted) which is sent back to be reprocessed.

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Concluding remarks as lessons learnt from the example - 1st concluding remark: all the info shown in the BFD are resulting from knowing more detailed models in regard to different chemical reactions happening within the reactor, plus other transformations later on required; e.g. separator is just resulting in a quantity of more volatile materials released to the outside environment (oxygen and CO2 carbon dioxide) … etc. (alias it is like saying: from knowledge/models in chemical engineering to knowledge/models in industrial engineering domain). - 2nd concluding remark: on the whole, we can understand that the model at higher abstract modeling level (BFD showing production flows) is constrained by what is happening in terms of physical / chemical transformations along the production process > we can synthesize that we are obtaining an initial analysis in terms of production flows which will then enable to define T/APC (theoretical/actual production capacity) considering that some material is also leaving the process (Oxygen, CO2, H2O) > 58673 kg/hr (> necessarily, some unavoidable material weight loss, due to the inherent process characteristics, may happen); any other variation in the process conditions may of course lead to further material loss (e.g. reactions should happen at given conditions such as temperature etc…, if standard conditions are kept, otherwise …) ….

2.1.2 Example 2

Flow sheet for the production process of Nylon 6,6 (continuous process)

From this picture we can’t understand a lot, we have to read also the notes but it’s not still enough. We have to be experts in this kind of things

Nylon-6 and Nylon-6,6 are two most important polyamides. In general, nylons come in many types, the two most common for textile and plastics industries are nylon 6 and nylon 6-6. The nylon production processes can be divided in two different classes: a) primary processes: the raw materials are oil based (from petroleum) and the process output is made of nylon chips; b) secondary processes: nylon chips are the raw material and the process output is made of plastic film, plastic rope or casted objects. In this regard, nylon has a broad variety of applications as e.g.: i) single wires for filtering fabrics in chemical industry, fishing lines, fish-nets, ropes, seat belts, food envelopes and containers, etc.; iii) (in textile) for hosiery, swim- wear, upholstery, para-chute cloth, umbrella cloth, etc. ii) (in plastics) polymer for injection melted mechanical components as gears, screws, etc. The example shown regards the primary process: in this case, Nylon 6,6 results by reactions of two types of components (diamine and dicarboxylic acid stored respectively in silos A and B); the reaction leads to create linear macro-molecules laid in parallel; more precisely, the reaction leads to form nylon initially as polymer molecules (oriented along an axis).

(short intro to flow sheet) The flow sheet is a process flow diagram, which is another type of representation typically found for process plants. Herein, the general production flow is displayed by showing the relationship between major equipment of a plant facility, not showing minor details such as piping details and designations; the blocks are not anymore rectangles but shapes which are resembling the original form of the equipment; arrows represent the production flows through the different equipment.

(back to the production process of nylon 6,6) Components are pumped into the first polymerization tower; the tower is kept at temperature 250 degree celsius and pressure 15 ata; under these conditions, organic molecules are forming chains; when they pass to the second polymerization tower their molecular weight even increases, leading at the end to polymer molecules; two towers are used > consider the relationship b/w flow (flow rate in meter cube / hours) and the processing time required for the chemical reaction (where tp is occurring at given standard conditions of temperature and pressure, as said) > this leads then to the definition of the required volume where the reaction occurs, and this V is high because tp is high > so separation in two towers.

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(Considering the importance of technological parameters) it is worth remarking that, when the two towers are built, volume V becomes a structural constraint; hence, if the flow is not regulated at the standard / nominal Q (e.g. lower than the standard Q) for which volume V was built, there is a need to leave more time for processing the material in the towers, which would then require some changes in the operating conditions (temperature, pressure …); this would lead to some variations of process conditions respect to standard, hence leading to different scrap rates (during the production regime).

(Continuing the process) the intermediate product, when the polymer molecules have been formed, is sent to the next stages of the production process, i.e. wiredrawing – leading to the formation of spaghetti like outcomes –, cooling / washing through water flows (eliminating impurities); afterwards, a cutting process enables to obtain chips (spaghetti are cut regularly to obtain small cylinders); eventually, the chips are transported up to the centrifuge which is used to dry the chips (eliminating water); in the last tower of post-condensation the molecular weight is still growing, and the chips are further dried, ending up into the storage silo.

Concluding remarks as lessons learnt from the example It’s a rigid production system, - it has been designed in an optimal way to produce a single kind of product, if the demand is going down or has a peak, we can’t adjust the production - According to the receipt, even if the ingredients are the same, if we change their quantities, we have different final products, and we need different transformations - We can’t produce different products at the same time: when we start from a certain receipt, we have to finish it, and then we can adapt the system to another receipt, and then start the new one

- 1st concluding remark: this is a clear example where the process plant is designed to operate as a continuous flow production process: all phases of the production process are regulated in strictly dependency and control of standard conditions should be kept at a production regime; This kind of system is still used also if it’s rigid, because it tries to achieve the best economy of scale: the fixed cost can be put on variable costs, so the concept is that this system is maximising the economies of scale; we can measure them in terms of productivity of production system - 2nd concluding remark: in this concern, it is worth pointing out that a warm-up period is required to achieve the production regime; the process conditions during the warm-up are not the optimal / standard one, therefore scrap is over-generated. Also for this reason, the type of plant is planned to produce on a continuous production cycle (24 H) for a production campaign of many months (e.g. 3 months) (to avoid high scrap rate every time the campaign is started). - 3rd concluding remark: if, in the plant, standard flow rate Q cannot be achieved, due to variations in target production volume / rhythms, there is need that the phases of the production process are regulated under different conditions, leading to different performances (with respect to standard conditions); the same considerations should be applicable if we change the product type; in general, high sophistications are required with new regulations / set-ups, leading to some costs (more scrap rate) even at regime, if we are not capable to achieve optimal / standard conditions > then regulate but at a cost which could not be neglected > low flexibility > that is: the range of production volumes / products is very limited, and the changes would be any how at relevant costs.

NB: for reaching the best economies of scale, we are not flexible -> flexibility is in trade off with productivity Sometimes the market is asking to produce a variety of products with a quite low costs: they should try to be flexible and to accept to be less productive, the trade-off is always there and cannot be solved

Production system designed for having a good production mix, accepting to have less volumes, is the batch-based production (Example 3). NB: the decision of the type of system is not up to the chemical engineer, which is design the plant, but it is a strategical/management decision.

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2.1.3 Example 3 Flow sheet for the production process of Nylon 6,6 (batch process)

From this picture we can easily see the starting silos (A and B) Rather than the picture before, we could identify also the areas of the transformations (such as cooking, drilling and post-cooking); moreover, we can identify three final machines, which are a kind of oven. Then the human is taking the cooked material and it is transferred through a line.

There are some dot-lines distinguishing the different phases This second picture suggest us a job shop, because it divided the different jobs/transformations into different areas

Differences: - We are not moving pieces, but containers full of materials - It’s a flow shop, the process has always to be done in a continuous way, the materials always start from the initial point and then arrive in the final warehouse - In the mechanical production we can have different order at the same time, here we have to follow one process per time

Nylon-6,6 can also be produced in batch processes. The two components (from silos A and B) are sent to an autoclave wherein the polymerization occurs (instead of the two towers); the production flow is then continuously flowing through a next line where wiredrawing, cooling/washing and cutting are executed; a direct transport still happens thanks to pipelines b/w silos of raw materials and autoclaves, as well as autoclaves and wiredrawing, cooling/washing and cutting; a buffer is present at the end of each line. BF is a decoupling point before the final stage, for drying and post-condensation made in batch tumbler dryer; in terms of operations, the batch is loaded onto the dryer, its operation has a duration until the batch of material is unloaded: during this time, the transformation required at stage s.6 is occurring, regarding all the material within the batch, while the equipment is utilized only by that batch. Similar issue happens before the BF: in autoclaves the batch is subject to polymerization process and then it flows to other phases. It is clear that the production is batch-wise processing. Since the production capacity is lower for each production equipment included in this plant design (lower respect to equipment making the continuous flow production of nylon 6,6), there are more equipment for the same stage: we have, of course, the possibility to plan the production of different products at the same time in more parallel lines (required to achieve the production volumes) and dryers after the buffer > batches of different products can be concurrently produced in the different equipment, e.g. we are concurrently producing N6,6X, N6,6Y and N6,6Z that are going to feed the correspondent storage BF > multi-model system. On the other hand, considering the operating cycles of the production equipment, each equipment may be producing, in different campaigns, different products: more intermittent management cycle, from batch to batch, different if compared to continuous campaigns / 24 H. Overall, there is a mid flexibility leading to a mid range in the production mix produced by the plant; there are obviously some costs of this flexibility e.g. reduced yields for many reasons, due to set-up to change product recipes, different regulations/adjustments, scraps … > (e.g. set-up) batch to batch variations require adjustment in polymerisation parameters to take care of such variations.

Concluding remarks as lessons learnt from the example 1st concluding remark: batch process is another solution when our strategy is based on flexibility (more product variety, market driven, …) and we can accept higher costs. Of course, flexibility is any how limited by many constraints (see for ex. some fixed routing b/w s.3, s.4, s.5.

In conclusion: - A system based on continuous flow has to be designed with big machines and pipelines - A system batch-based could be designed with some machines similar each other, divided in different areas quite as in a job shop

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PROCESS PLANTS – GENERAL FEATURES - Simple production logistics - Simple production management - High plant utilization and equipment efficiency - Low need for workforce - Qualitative characteristics of products are stable (when process conditions are kept stable) - Low flexibility - High investment needed - High risk of obsolescence - Significant impact of failures - Importance of variations in process conditions

For what concern logistics within the plant (production logistics), this is a natural consequence of the fixed technological routing, resulting in the plant structure. - pipelines (including pipes which means also a set of instrumentations along the pipes, required to control the transport of the materials), operated/used both in continuous and discontinuous flow transformation; of course, not all is made by means of pipelines, also some transport system are used, more based on serial transporters, as trucks, dumpers, trains etc. (see the case of a copper mine and transportation of extracted materials > the extraction of raw material can be both underground i.e. sinking a vertical shaft into the Earth to an appropriate depth and driving horizontal tunnels into the ore, or open pit i.e. 90% of ore is mined by this method; ores near the surface can be quarried after removal of the surface layers); - in general, the production logistics can be considered simple, first of all because it is majorly designed/built into the plant structure, with few management decisions still left on the routing side; furthermore, products are few product variants, and may require few materials within the product recipe (taken from some silos concentrating those materials); overall, movements can be done in relevant batches (as dumpers) or by continuous transport activities b/w stages or stages and storages (along pipelines, so back to routing built in the plant design). All in all, not as many discrete components moved, as loaded units to be moved through the factory, as happens in manufacturing.

First of all, for what concern production management of the plant, this is limited to some decisions. Management decisions are limited to two main problems: batch sizing + batch sequencing within a production campaign. The decision is the number of production campaigns / number of batches (hence, batch sizing) to be produced for each single product (i.e. short digression to better understand this management decision > this is related to the typical set-up/cost of inventory holding costs optimization > when the number of production campaigns / batches is decided (e.g. by using Magee Boodman’s model), the batch size is also defined, being equal to Dj / No (i.e. demand of product j / number of production campaigns where, for each campaign, only a single product is produced)); batch sequencing is needed when different products are realized by the plant (also relevant to optimize if a sequence dependency exist).

High production equipment utilization / efficiency are mandatory characteristics: - high production volumes + stable volumes through time are required to achieve an economically- reasonable investment -> in fact, the fixed cost is high/very high in this kind of plant > more precisely, economies of scale can be better achieved with higher plant sizes which implicate high volumes (and high investment/fixed costs) > as a consequence there is also the «mandatory» need to continously produce (i.e. high utilization) at this high volume (24 H 7 days possibly), in order to actually achieve the advantages of economies of scale (i.e. distributing the overall fixed costs to high production volume); - therefore, efficiency losses cannot be acceptable and they are reduced to some few factors, like few set- ups for new production campaigns, few scraps, few unexpected stoppages due to failure …; when there is a batch process, more inefficiencies are due to the inherent characteristics of this type of production (intermittent with batch changes, with different products, possible needs to regulate production equipment with product change-overs, potential scraps at warm-up).

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Other typical characteristic is the low presence of workforce: - the system design is clearly based on high automation, as required for process control (of process variations); - the tasks of operators / workers are limited to some activities as control activities (control room), maintenance, logistics with serial transporters (e.g. dumpers).

Regarding quality issues, as discussed this depends on the stability of process conditions: - Keep stable conditions during the production phase; - Limit the transients as warm-up which are usually associated with scraps.

Low flexibility is clearly a characteristic of this kind of plants concerning different flexibility dimensions and for many reasons. Even in the most flexible solution (batch process production) we have: - limited set of products, batch wise production (due to batch sizing and sequencing, first one product type for a campaign, then another product type, etc.) > limited mix flexibility > it is any how still today challenging to be «market-driven»; - a plant is not easily (re)configured / (re)converted because of the fixed plant structures (i.e. piping …) + the high cost of the plant shutdown (remember the need for continuous production to reach economies of scale) > limited expansion flexibility > this is done any how; a plant is revamped in some parts for its aging or, some times, it is subject to reconvertion in order to keep in pace with new requirements and technological developments that enables the achievement of those requirements (e.g., environmental objectives on impacts + improvement of some performances due to technological upgrades with new technological issues >>> i) cite the BAT, even if BAT should be normally considered at the begin of life, while upgrades are along a very long life of the equipment > often more decades; ii) again the case http://pascagoula.chevron.com/home/abouttherefinery/whatwedo/processingandrefining.aspx, it mentions some upgrades; - due the high required investment, this type of plant is usually built to work on more production shifts / high number of production shifts per week (24H/7D)> hence, a small demand variation cannot be absorbed at all, if not changing some speed parameters (@ risk because we may cause scraps and any how not optimal process conditions); remaining shifts or overtime are normally few or not any at all > limited volume flexibility;

Other characterisics: - High investment needed > as said, in order to achieve higher economies of scale, a trend was observed towards increasing plant sizes and capacities > inducing very, very high investment costs; on the other hand, there are some new trends which are actually observable on small-sizes of this kind of plants, which means of course orienteering to other objectives, relating to product diversification and more market driven approach. - High risk of obsolescence > there is a clear high risk of obsolescence with the limited set of product types (or one type) > facility lifetime is strictly related to products’ lifetime; this is a general concern, which exist in these plants, and it is evan amplified (respect to manufacturing); - Significant impact of failures > primarily, there is a series logic in this type of plants, with some degree of parallelization / reduncancy, but not much + presence of relevant buffers (with high materials / WIP stocked therein) just in the case of batch processes, which are of course useful in order to protect of failures (while occupying high spaces/high WIP, but this can be considered a minor concern respect to the problem of failures > also because the value of WIP could be not high, being the product/intermediate a commodity); in the case of continuous flow production of course an unexpected shutdown is really really critical (also for safe issues); - Importance of variations in process conditions already discussed and a clear intrinsic challenge of process plants.

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ROUGH DESIGN OF A PROCESS PLANT (CONTINUOUS FLOW) It’s quite simple; we should know the technological roughing and also the production equipment;

36. Define the production flows according to the technological routing required for the product 37. Identify all the production equipment types that are needed and the bottleneck 38. Define the theoretical production capacity TPC [ton/hour] Where TPC = theoretical production capacity in [ton/hour], or other similar units, i.e. [kg/hours] We have to design a plant, and in order to define it, we should know how many products it will provide us -> capacity of the production system; typically, we measure the capacity in terms of materials which is flowing, so as kg/hour or tons/hour In this way we obtain the total production capacity, but it should be corrected considering some prudential coefficients Calculate the actual production capacity 퐴푃퐶 = 푇푃퐶 ∗ 퐴 ∗ (1 – 푆푅) [ton/hour] where o A = line availability (0 < A <= 1) -> way to measure the fact that an equipment, or group of them, or the system, could be broken, so the system will be less available than the 100% (maintenance, repairing…) we should consider the system availability impact on production capacity o SR = scrap rate (0 <= SR < 1) (varying according to the process conditions kept in the system) -> in the movement of material could happen that something will be wrong: some part of the material of the flow is not good enough, or it has to be reworked, or it has not the expected characteristics, so cannot be sold or should be rethreaded; it’s normal in this type of industry, to consider a percentage of scraps We will design the system on the actual production capacity; this is a setting decision: we are setting how much our system should produce 39. Compare the actual production capacity and the demand. If necessary, modify the line and go back to step 2 The final decision of a design engineer is to buy or not to buy equipment, and also how many of them, we are deciding what we have to buy in the market

2.3.1 Steps of system design - case of one product - Steps 1 – 2 basically these are dependent on the knowledge of the process (e.g. chemical engineers) and the subsequent constraints; an industrial engineer can basically understand but it is dependent on the technological options available on this side, and constraints; - Step 3 – 4 once he/she has understood, the industrial engineer can basically support the study of the plant structure, starting from the bottleneck, in order to calculate the APC > Hence, (understood the process constraints) a first clear indication is available on the bottleneck for the production flows > TPC is known > therefore an evaluation of APC based on SR and A (concepts of coefficient losses). - Step 4 remember the fact that the SR may be dependent on the process constraints -> if we do not operate at standard process conditions (i.e. either warm-up or different conditions from process conditions at the nominal / standard regime), the SR may be a different value, respect to the best value; - Step 5 few options may be available, for ex. duplicating some equipment but this should be clearly verified with knowledgeable engineers on the process.

ROUGH DESIGN OF A PROCESS PLANT (BATCH)

2.4.1 Assumptions - Production in batches (batch A, batch B, batch C and so on); The equipments are used according to the batch wise processing approach: batch A of a product, then batch B of another product, etc. >>> to change from one batch to another, it is required a setup for the new campaign (with the new product). - Setup times are required and do not depend on the production (batch) sequence Set-up times are considered sequence independent: this could be either because in reality there is no sequence dependence (negligible), or it is the result of an optimization procedure that enabled to identify best batch sequencing (i.e. first batch A, then batch B, etc.) to reduce set-up times > in this last case, set-up times are given by assuming the scenario of optimal sequence.

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Design a production system which will produce batches by batches it’s not the same of designing a job shop, but it’s related to the same basic concepts: how many operators we need, how many hours we need, how many setups we have to do…

2.4.2 Steps 1. Identify the production mix 2. Define the production flows according to the technological routing required for the products (in the production mix) 3. Identify all the production equipment types that are needed 4. Calculate yearly workload and number of hours available for each type of production equipment i 5. Calculate the number of production equipment of type i necessary to produce the production mix

Of course, there is a production mix (any how within a limited range); considering that some functional departments can be identified in this kind of plant (i.e. autoclaves, tumble dryers … in the nylon batch processing), we can adopt similar formulation as the job-shop case. By analogy, the steps are self-explaining.

2.4.3 Yearly workload NHi for production equipment i 푁 푄푗 1 푁퐻푖 = ∑ ( + 푆푇푇푖푗 ∗ 푁퐶푗) ∗ 푇푃퐶 ∗ (1 − 푆푅 ) 퐴푖 푗=1 푖푗 푖푗 where - i = index of the equipment-type - j = index of the product-type - N= number of different product-types - TPCij = theoretical production capacity [ton/hour] - Qj = quantity of product-type j that has to be produced [ton/year] - SRij = scrap rate (0 <= SRij < 1) - STTij = setup time [hours/setup] - NCj = number of campaigns of product-type j [batches/year] - Ai = availability (0 < Ai <= 1)

Coefficients (measuring time losses, cfr. Turco) Observe that only relevant, typical coefficients should be considered wisely because we have to apply to the problem of the case > e.g. the HC is not considered > there is no clear machine interference problem as the manufacturing case; on the other hand, the intervention on the production equipment is clearly possible (even if not desirable) for a shutdown > maintenance. In the job shop formulas, there was also human coefficient, because there were a lot of operators working in it; in theses formulas we don’t find this coefficient because this type of plant is mostly automated, the operators are just loading material and controlling the flow, they not directly working on the material, they are not doing some performing activities, so we could not consider it, because its role wont’ have a big impact on our design, and considering them could be just a loss of time

- Scrap rate SR: percentage of materials out of tolerance (not achieved the target quality) - Availability: percentage of up time (intervals), when the machine is required for production and actually available to work (w/o trials), with respect to the total time (up time + down time); down time intervals regard the overall failure and maintenance downtime.

Observe also that here we are using the TPCij (not Tij as in the job formula) > this is the production capacity for a given equipment i, supporting the chemical-physical transformation of product j at a given step in its routing > here we are not talking about a single workpiece manufactured as in the case of the job shop …

Applying the formula, the yearly workload / required capacity NH takes into account the need to load the machines (on yearly basis). Thanks to the coefficients, NH also considers the presence of time losses within the machine calendar time > thus leading to a gross / effective workload required from the machine.

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Few quick notes: - STT is long hours or day (using hours is a better, practical measure); - one campaign is normally coincident with one product batch; - number of campaigns NC may be also different for products from equipment to equipment, one different case can be then also expressed as NCij.

The number of setup needed depends on the size of the batches, as in the job shop, but in this case we don’t have directly number of batches, but Number of Campaigns NC: production runs by campaigns, not batches by batches; there are campaign of products, valid in the oil, food, chemical, pharma industry Moreover, we should know that machines could be broken, so we have to consider the availability estimated for each single equipment

2.4.4 Number of hours available for each type of production equipment i 퐴퐻푖(푠) = 푊퐻푖(푠) ∗ 푆퐸 where - WHi(s) =yearly working time available (depending on the number of shifts per day) - SE = scheduling efficiency (0 < SE <= 1)

(see back the difficulty of production management) > scheduling complexity is not high + it would be mandatory to keep high utilization > scheduling system should perfectly utilize all plants > so SE can be considered high; it is not high because of some complexity induced by the different product routing and some constraints along the process.

2.4.5 Number of production equipment of type i necessary to produce the production mix 푁퐻푖 푁푀푖(푠) = 퐴퐻푖(푠) This is the same formula of job shop: having the number of needed hours and available hours, we can calculate the number of needed equipment

ROUGH DESIGN OF A PROCESS PLANT (CONT. FLOW/BATCH)

2.5.1 Evaluate the yearly costs 푂푣푒푟푎푙푙 푝푙푎푛푡 푐표푠푡푠 ∗ 푚 + 푂푣푒푟푎푙푙 표푝푒푟푎푡푖표푛푎푙 푐표푠푡푠 - Overall plant costs include the costs of all the production equipment acquired to build the plant; - m = coefficient used to split costs on plant/facility lifetime; - Overall operational costs may include different types of cost, i.e. typically energy costs, maintenance costs, raw material costs, ….

(financial perspective) CAPEX versus OPEX > CAPEXs are splitted during the facility / machine life time > splitted cost can be then comparable (so, summed up) with costs representing OPEX. The mechanism to split is based on financial issues not detailed in this course. Comments on the typical costs: cost of buying equipment and also the cost to run a machine (operational costs) should be considered

3 ILLY CAFFÈ - An example of a process industry - ASME diagram (do it for yourself) - Layout (do it for yourself) ➔ What are the main characteristics of a process plant?

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1 DEFINITION OF SIMULATION Simulation is the imitation of the operation of a real-world processor system over time. We want to simplify the behaviour of a system, trying to predict it

Computer Simulation is a technique where experiments are conducted on a computer in order to recreate over time the functioning of a system. Time is a key word: we want to simulate something that is happening in times; the content of the simulation is a real process or a system, it is dynamic, it can change over time, it depends on the time of the system

This experimental technique allows us to predict the behaviour of a system under certain conditions that most likely will manifest while the system operates

Simulation is, first of all, a modelling technique (that enables to abstract a real system and experiment its functioning before any prior implementation): originally developed in the area of Operations Research and, over the years, found application in various sectors (…).

Considering manufacturing there are different possible application fields: - (depending on the types of system under concern) from product/asset simulation to manufacturing system (i.e. factory floor – warehouse level) and supply chain simulation; - (depending on levels of decision-making and analysis) from operations management to operations and business management and to a more global level (e.g. from factory -> to organization -> to impact on the environment).

Within the enterprise system (i.e. from operations to business management), it is worth noting that: - in most business environments, it is evident that changes at one level of business management will have an impact on others, operations management; - there are (simulation) techniques & tools that could be used at more levels of analysis and decision- making, so simulation can regard different levels.

It is essential the development of computer support: nowadays it can be put in practice with acceptable time for the computation, and indeed it would not be possible to support decisions by hand simulation.

1.1.1 Why Simulation? We need simulation to assess scenario, to understand what happen if something happens (what-if analysis). We have to take decision about something that did not happen, we need to understand how possibly the system will behave, in order to assess the behaviour of the system; ex: how many components should I take for the warehouse in order not to go in stock out; I need to order a quantity for the warehouse without knowing the demand yet

Since its inception, simulation has been adopted in various sectors, as manufacturing, services, defense, healthcare, and public services. Simulation has been adopted also outside the manufacturing world, we use it in every context (not very much in product development, because we don’t have a lot of information on the company); there are some context in which we have to take decision before and therefore we need simulation

Simulation is known as one of the most widely used technique in the field of Operations Management. Simulation is considered as a relevant modelling technique to support different types of decision-making.

1.1.2 How? We have to do data based and rational decision, we need reliable data Computer has supported the use of simulation in practice, as computer-based simulation tools and techniques have been developed over the years.

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SIMULATION AND MODELLING - Simulating means to recreate the behaviour of a system (e.g. production system) over an extended period of time, in a shorter (simulation) time; we need to simulate to have information in small-time - To simulate implies the construction of a model of the system analysed

Is not always possible to make a perfect model, sometimes we can just have a very good model, we will need some approximation - The input is the independent variable - The output is the performance variables, in terms of costs, times, number of pieces, quality level

Model is putting into relationship independent variables (factors) with the performance variable (objective functions and outcomes)

1.2.1 What’s the meaning of simulation, then? The problem is that we are living in the reality, we have to turn the real system into an abstract model ex: a series of machines through which the products have to go - Experiments: what happen if I put 100 hundred components in these machines - Numerical result: in order to process 100 hundred components, you will need 1 days with n machines

The numerical result can help us in understanding what we can change in the real system to improve performances, we need to understand if it suitable with the real system

Simulation is considered as a relevant modelling technique to address complexities of a system of interest. In the real system we cannot understand everything, some information cannot be modelled, we are simplifying representationn of a real system in order to better understand it We use model to simplify things, and we use models to make analysis and predictions Complexity are sometimes given by the structure of the system, because it’s complex itself or it’s very dynamic [If we can measure everything we go for analytical models]

THE CONCEPT OF SYSTEM - A system can generally be defined as a group of entities (elements or components) that interact each other; these entities are not just people, but we have interaction between components, machines… - Main characteristic of a System o Several elements interaction o The overall behaviour depends on individual behaviours: if one machine in the middle broke, overall the system can stop; sometimes, some individuals affect the most part of the system, while other are not so important (ex: there is just one machine working only one component)

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HOW TO STUDY A SYSTEM Different ways to study a system Sometimes we experiment with the model; this model could be physical (3D model), or could be mathematical, which could have - analytical solution -> we can really measure everything in detail - experimental solution -> we can’t have or measure in the reality, so we need simulation We have to make experiment in order to

understand the system

1.4.1 Types of Systems - Discrete: Systems where the status variables change instantaneously at discrete intervals of time ➔ Physical component, shop system, IT systems, manufacturing systems, traffic regulation systems ex: in the class, counting the entering in the classroom, we have to describe it with one enter, we wait time, someone else enter, we do not have continuously people going out or in the system

- Continuous: Systems where the status variables change continuously during the time of simulation, we can measure instantly the variables of the system ➔ Flow of fluids, heat, etc…

1.4.2 Analytical vs Experimental Models - If the relations the system is built on are simple enough, it is possible to use mathematical models (algebraic, calculus or linked to probability theory) to get an exact information. - However, the majority of systems are too complex to create realistic analytical models.

➔ Analytical Solutions Y = f ( X ), if we can describe in a perfect/precise way ➔ Experimental Models through simulation ex: if I have one shape system, I go to the machine A and try to create a model; if things are complicated, I need different way to create a model. They are of course functions, and there are simulations to measure them

1.4.3 Deterministic vs Stochastic Models We have two different ways to model a system: - Deterministic: There is no uncertainty in the simulated phenomenon, we are not unsure about the phenomena we measure o Customers arriving at regular intervals of time o Preventive maintenance interventions executed at regular intervals of time (with no variability) we do activities to do maintenance at specific intervals of times, distance etc… Stochastic: There are some aleatory variables, that are generated within the model through proper statistical routines; ex: we do maintenance when something has broken, this is an aleatory variables that we have to generate in our model, with randomly value in the simulation; since the variable are random, the model will not be 100% accurate/precise

TYPES OF SIMULATIONS - Static versus Dynamic Does time play a role? The dynamic the variables change over times - Continuous versus Discrete Do state changes take place continuously, or instantaneously at certain point in time? - Deterministic versus Stochastic Is there randomness in the inputs or operations of the model? we will use model to do what-if analysis, in order to understand system, applying these results on the real system

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2 DISCRETE EVENT SIMULATION

DES – DISCRETE EVENTS SIMULATIONS INTRODUCTION Process is a sequence of activities; System is a group of entities interrelated, or a group of processes as entities; Simulation is the imitation of the operation of a real-world process or system over time.

- Computer Simulation is a technique where experiments are conducted on a computer in order to recreate over time the functioning of a system. - This experimental technique allows us to predict the behaviour of a system under certain conditions that most likely will manifest while the system operates. - Since its inception, simulation has been adopted in various sectors, as manufacturing, services, defence, healthcare, and public services. - Simulation is considered as a relevant modelling technique to support different types of decision making. - Simulating means to recreate the behaviour of a system (e.g. production system) over an extended period of time, in a shorter (simulation) time - To simulate implies the construction of a model of the analysed system

2.1.1 How? Computer has supported the use of simulation in practice, as computer-based simulation tools and techniques have been developed over the years.

2.1.2 Industrial Simulation - Digital Factory Into manufacturing (production, logistic, management) simulation supports: - Design of new systems/solutions, ex: I have to simulate to decide to purchase a new system - Improvement of actual systems/solutions ex: we have a bottleneck, we can increase the number of operators, working hours or machines - Performance analysis , to assess the performance we should have (e.g. productivity, bottle necks, resources saturation) - WHAT-IF analysis: how outputs (performances) are changing in accordance to variation of some process parameters (input). I can estimate different scenarios, I want to see what happen if I change the inputs - Training

DISCRETE EVENT SYSTEMS Discrete events systems (DES) are: - Dynamic systems (over time) which update their values only at discrete number of points; ex: starting status is 200 people inside the room, the system changes only in specific moment of time, not equally distribute (not every 2 minutes someone enter the system) - No continuously changing states are of importance.

Examples of DES: - Call centre we have some specific time when call gets in - Airport - Gas station the distribution of fuel is not constant - Factory - Class the rate of arrival is fixed and not predictable sometime - Warehouse - Restaurant we have peak hours, not specific constant time

DES approach: - We focus on the time between the events. - Having the knowledge of the time of next event we can move along time line and update the system only at this specific time point. - Since we know that nothing has happened between the two time points, we have full information about history. - Events are changing the system; we can model the events and the time between different events

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2.2.1 DES – Definitions of Main Components Elements/distinguish element when we dealt with simulation: - Entity: a thing with distinct/independent and temporary existence that passes through a system. e.g.: a piece that should be assembled (as a component), a client to the bank office (NB: if we have 5 customers, we have 5 different entities), something that enters my system, is processed and exits my system - Resources: things with active and permanent existence that provide a specific service to entities e.g. machine tool, conveyor, a banker, … NB: Not always each entity uses all the resources, it depends on each system and case - Queues: things with temporary and passive existence that are formed by entities which are waiting for a resource (that is not free at that time). We have an entity inside a machine, and another entity is waiting to enter in that machine; every time we have something waiting, we will know the number of component in that line in that moment - Variables and Attributes: data and information about entities or resources e.g. warehouse capacity, cycle time You will have to model/build the production plant with specific characteristic of sources: cycle time, the time to drill… there are information linked to specific resources in a specific system We are including this information to model the system: how many resources do we have? Which is the distribution of the arrival?

- Status: Description of all the values attributes of an entity or a resource, in a specific instant of time. - Event: Period of time in which the model status is changing (change of status of entity or resource). - Activities: Operations done during an event (started and ended).

SIMULATION PHASES

- We have real problem or system to improve. - We are generating the conceptual model, to understand which are the variables, entities - We have the computational model to run the calculation, try to apply the model; at the end we do the experiment, changing the characteristics - We see the solution in the real system, and at the end we give feedback to the real system

2.3.1 Real System - Problem Definition - We have to identify objectives and constraints - We have to define a project plan o choose the different simulation’s scenario o project time, which are the scenario o resources, team and different roles.

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2.3.2 Conceptual Model - Detail and accuracy of the model - Variables (e.g. production plant design and sizing) o exogenous variables (external cause, e.g. processing times) o decisional variables (e.g. machines numbers) o endogenous variables (internal cause, e.g. saturation rate) - Constraints - Performance Measurements o endogenous variables o choose the objective functions.

We have a trade-off between the accuracy and the level of detail The accuracy of the model should be higher as possible according to the level of detail we chose, but not too high for giving bas results Of course, not everything is measurable, so the accuracy will not be perfect, we are not arriving at 100% of accuracy, or we will have analytical model

DATA COLLECTION - Data collection is sometimes quite hardworking (what about digitalization?) Sometimes it takes lot of time to collect data, we can simplify the data collection process ex: how time to serve the sushi at the bar? You can go to measure based on the size of plate, the order dimension, the server of the meal, different rate of service, or we can measure through sensors, based on the weight of the plate - Data quality influences model quality (GIGO effect = garbage in, garbage out) if you give the wrong data as input in the model, the output will be wrong as well; we should be accurate and correct in the collection of the data - If some data are missing, we have to adjust the level of accuracy of our model. - If we do not have enough experimental data, we can use some statistical distributions.

SIMULATION SOFTWARE - General-Purpose Languages; these languages can be based on: o procedural (Fortran, C, Pascal, Basic) o object-oriented (C++, Objective C, Java...) - Simulation Languages: Siman, Slam, Modsim - Simulators: simulation packages, which use the previous languages to simulate (PlantSimulation, Arena, Simul8, Matlab-Simulink)

2.5.1 Choosing the Software There are different options, and each of them provides different performances; the chose depends on the needs we have, what we want to simulate, and which characteristic or simulation should have Evaluation Criteria; you cannot consider all these criteria at the same time, no one of these software is maximizing all these criteria - Flexibility - Animation - Interface with other data (ex: - Ease of development - Output visualization possibility to input Excel data or - Model execution speed - Statistics other data) - Reusability - Cost - Customer support

Independently by the choice, the software has to be able to instantiate the different parts of the system (entity, resource, queues, attributes) and to describe the different behaviour of the them and the system (status, events, activities).

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MODEL ASSESSMENT AND VALIDATION Since we are making a model, it will not be 100% accurate, but compatible with the level of accuracy that we want - Assessment: accuracy, completeness and consistency of the simulation model respect to conceptual model that we want to assess. -> it’s between models The conceptual model is created by me, the simulation model that I create should reflect the reality ➔ Did you do things right? - Validation: accuracy, completeness and consistency of the simulation model respect to real system. -> it’s between model and system ➔ Did you do the right things? I can be very precise and accurate, but the model could be not rightly related to the real system

3 MONTE CARLO SIMULATION

LET’S START WITH DEFINITIONS

3.1.1 Simulation: fictitious representation of reality [0……...... 0,5……...... 1] We have a coin, we can have head or tail When we do not have all the information of the system, we have distribution of the variable 39 Drawing one random number from [0,1] can simulate the tossing of a coin (Head <=0.5, Tails >0.5).

We make a general simulation; we want to draw the behaviour of the system linking a simple model to it This is a simulation, not a Monte Carlo Simulation!

3.1.2 Monte Carlo Method: technique that can be used to solve a mathematical or statistical problem How many head and how many tails? We can drop the coin 15 times, or you can select 15 random number between 0 and 1; if I drop a series of coin, I make a system behave and then count

Pouring a box of coins on the table and computing heads/tails is a Monte Carlo Method of determining the behaviour of repeated coin tosses but is not a simulation. ex: I I want to toss the coin 50 times, how many heads will I get? We use random number to perform the simulation, so I take random numbers between 0 and 1 for 50 times -> the counting of the single random numbers which simulate the behavior of a system is the Monte Carlo simulation.

Monte Carlo Simulation: uses repeated sampling to determine the properties of some phenomenon – or behaviours.

Drawing a large number of random numbers [0,1] and assessing the behaviour of repeated coins tosses is a Monte Carlo simulation.

Is a technique used to solve stochastic problems. The model is used when the model is complex, not linear and with many uncertain parameters.

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WHY “MONTE CARLO”?

The term comes from Monte Carlo’s (Monaco) casinos “The first thoughts and attempts I made to practice [the Monte Carlo Method] were suggested by a question which occurred to me in 1946 as I was convalescing from an illness and playing solitaires. The question was what are the chances that a Canfield solitaire laid out with 52 cards will come out successfully? After spending a lot of time trying to estimate them by pure combinatorial calculations, I wondered whether a more practical method than "abstract thinking" might not be to lay it out say one hundred times and simply observe and count the number of successful plays. This was already possible to envisage with the beginning of the new era of fast computers, and I immediately thought of problems of neutron diffusion and other questions of mathematical physics, and more generally how to change processes described by certain differential equations into an equivalent form interpretable as a succession of random operations. Later [in 1946], I described the idea to John von Neumann, and we began to plan actual calculations.” Eckhardt1987

MONTECARLO CHARACTERISTICS - Monte Carlo Method is a technique that requires the use of random numbers to solve stochastic problems on a static system. - A Monte Carlo Simulation model can be conceived as an experimental system, where each simulation corresponds to an experiment

Indeed: - It is not always possible to have real experiments where fenomena take place ➔ nature can't always provide us aleatory situations - Monte Carlo simulation uses random numbers generated from the computer to simulate multiple times the aleatory phenomenon - In this way data are rapidly collected to be processed with statistical analyses ➔ the higher the number of “experiments” the more reliable the outcome

Generally, a computer simulation is based on models that imitate reality and elaborate predictions. For instance, by using Excel there will be a certain number of parametric inputs and several equations that elaborate some input into output.

Monte Carlo Simulation works iteratively, by evaluating a deterministic model that uses a set of random number as input. This kind of method is often used when the model is complex, not linear and with many uncertain parameters. MCS can be directly used to analyze ‘static’ problems or to solve numerical problems featuring a stochastic nature (e.g., in property valuation, risk management). NB: if a machine has a precise time, I don’t use Montecarlo; we use it when we have more randomly variables

ELEMENTS Fundamental elements to develop a Monte Carlo Simulation: 6. Information on statistical distribution expected about the uncertain elements on the simulated process; we will use different types of distribution, as triangular or Bernoulli distributions ex: cards, I do not know exact if the card is the next to be played, I have a statistical distribution of arrivals of a specific cards, based on the card I have and the number of cars in the deck: I can estimate which are the probabilities of some events 7. Generator of random numbers, between 0 to 1, we need to convert this random number into its meaning; be careful, usually the software do not create a real random number, if you launch the simulation, close the software and then reopen and then relaunch the simulation, the results could be the same, because the system has some algorithms (ex: MATLAB and Excel) 8. Mathematical representation of the simulated process 9. One or more aleatory variables as output 10. Possibility to statistically evaluate the results; we will run a lot of runs, so the results should be statistically significant NB: the purpose of the simulation is to give the behaviour of a system, in order to take decisions on it

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SAMPLING METHOD 3.5.1 Monte Carlo Simulation (MCS) in business processes Of course, the simulation for production process and business process are the same, but usually a production system is something fixed, instead a business process is more difficult because it isn’t so physical, you have to be sure to have understood everything It is used to model the stochastic nature of activities in a business process (accordingly with their stochastic laws).

3.5.2 Procedure 11. Generate a sequence of random numbers; 12. Convert the sequence of random numbers into the sequence of values assumed by a variable of interest. In the case of coin, the variables of system were head or tail; in terms of machines, the variables could be working or not working, or in and out, components available or not available… You need the right number in order to figure the right variables It can be implemented even in simple tools such as spreadsheets (e.g. MS Excel) or more advance (as MATLAB). The causal values so generated (random numbers -> random variables of interest) are then used by the mathematical model (i.e. h(X1, …, Xn)) built in order to calculate the performance of interest.

3.5.3 Inverse transform method Algorithm to implement the method in MS ExcelTM In case of discrete probability distribution (thought histograms): - Generate (automatically) random numbers (between 0 and 1) -> in MS Excel™, CASUALE () or RAND() The random numbers could be used to simulate yes/no model, but also when the variables have more than 2 different values - In MS Excel™, function SE or IF (nested functions) to find the value x (knowing r) o 퐼퐹 푟 < 푝(푚푖푛) → 푥 = 푚푖푛 o 퐼퐹 푟 ≥ 1– 푝(푚푎푥) → 푥 = 푚푎푥 o otherwise 푥 = 푚표푑푒.

ANALYZING BUSINESS PROCESSES Using MCS for risk analysis in business processes: This is important because usually it - assessing uncertainties in business processes is within the mind of the Manager, - forecasting the performances of business processes so you have to understand the - reflecting on the underlying reasons of performances reasons that push him in doing a ➔ MCS:= stochastic simulation for operational risk analysis certain analysis

EXAMPLE - A QUIET WEEKEND … OF FEAR Friday afternoon, 2 pm, a large TO DO list: - Complete the calculation of weekly profits Is it possible to be at home by 6.15 pm? - Complete the report of weekly sales What should I tell my partner? - Submit the report to the supervisor The question will not be yes or no, - Go to collect the tickets for the theatrical performance we will obtain the probability of yes and no - Go to the minimarket for the weekly purchase

3.7.1 Model defined for analysing simulated scenarios Min Most likely Max Montecarlo simulation is based Complete the calculation of weekly profits 60 75 100 on distributions Complete the report of weekly sales 30 50 75 Submit thereport to the supervisor 1 10 30 We need to understand the Amend the report 10 20 35 sequence of the activities, then we start to do some calculation Go to collect the tickets for the theatrical performance 5 10 15

Drive to the minimarket 40 60 90

Go to the minimarket for the weekly purchase 25 40 55

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Based on data / estimates related to each activity, let’s simulate the TODO list (*)

(*) By means of MCS -> generating the random variables of interest, based on known probability distributions (min, mode, max)

We are calculating with a simulation a random number, that is choosing for us whether he is succeeding in complete; note that some activities do not require the end of other activities We will not calculate the average number, we use the distribution of the values

Before 5.30 pm 7% Output of the MCS of the business process (i.e., forecasted performance of the Before 6.00 pm 11% business process) Before 6.15 pm 51%

Before 6.30 pm 97% If the performance is not satisfactory, the process may be changed. Before 7.00 pm 100%

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