Applying the Supervisory Control System and Data Acquisition (SCADA) to Monitor Production Processes in Baghdad Soft Drinks Comp
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Lean Manufacturing in a High Containment Environment
IPT 32 2009 11/3/10 15:48 Page 74 Manufacturing Lean Manufacturing in a High Containment Environment By Georg Bernhard A case study of how Pfizer’s Right First Time strategy helped overcome at Pfizer Global daunting capacity challenges at its new large-scale containment facility Manufacturing at Illertissen, Germany, while Six Sigma and Lean strategies enabled the site to achieve previously unknown levels of efficiency. In late 2006, Pfizer launched its smoking cessation film-coated tablets. All of the process stages (granulation, product varenicline, known as Chantix® in the US tableting and coating) are controlled and monitored from and Champix® across Europe. According to IMS a separate control room so that employees do not come benchmarks, Champix® was the fastest product launch in into contact with dust that might be generated during the the European pharmaceutical industry, with marketing tablet production run. Transport is handled by automated, in 16 European countries in a five-month period. As well and entirely robotic, laser-guided vehicles. Operators as creating rapid and unprecedented consumer demand, monitor and control all containment room activities from the product launch also brought capacity challenges for a separate control room. Pfizer Inc’s small-scale IllertissenCONtainment (ICON) facility in Illertissen, Germany. The facility’s innovative IT systems integration enabled an extraordinary 85 per cent level of automation (LoA), A strategic site in Pfizer’s global manufacturing network, outstripping even the ICON facility’s extremely high 76 per Illertissen is focused on oral solid dosage forms and is a cent LoA. Thus, in NEWCON, all process sequences centre of excellence in containment production. -
Automationml 2.0 (CAEX 2.15)
Application Recommendation Provisioning for MES and ERP – Support for IEC 62264 and B2MML Release Date: November 7, 2018 ID: AR-MES-ERP Version: 1.1.0 Compatibility: AutomationML 2.0 (CAEX 2.15) Provisioning for MES and ERP Author: Bernhard Wally [email protected] Business Informatics Group, CDL-MINT, TU Wien AR-MES-ERP 1.1.0 2 Provisioning for MES and ERP Table of Content Table of Content .............................................................................................................................................. 3 List of Figures .................................................................................................................................................. 6 List of Tables .................................................................................................................................................... 7 List of Code Listings ..................................................................................................................................... 11 Provided Libraries .................................................................................................................. 12 I.1 Role Class Libraries ............................................................................................................................ 12 I.2 Interface Class Libraries ..................................................................................................................... 12 Referenced Libraries ............................................................................................................. -
Implementation of Lean Six Sigma Methodology on a Wine Bottling Line
MASTER THESIS The implementation of Lean Six Sigma methodology in the wine sector: an analysis of a wine bottling line in Trentino Master Thesis in Industrial Engineering by Sergio De Gracia Directed by Prof. Roberta Raffaelli Academic Year 2013-2014 Table of Contents Abstract ......................................................................................................................................... 9 Acknowledgements ..................................................................................................................... 10 Introduction ................................................................................................................................ 11 Lean Manufacturing .................................................................................................................... 14 1. Lean Manufacturing ................................................................................................................ 14 1.1. TPS in Lean Manufacturing.......................................................................................... 15 1.2. Types of waste and value added ................................................................................. 16 1.2.1. Value Stream Mapping (VSM) ................................................................................... 18 1.3. Continual Improvement process and KAIZEN ............................................................. 19 1.4. Lean Thinking ............................................................................................................. -
Management Science
MANAGEMENT SCIENCE CSE DEPARTMENT 1 JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD Iv Year B.Tech. CSE- II Sem MANAGEMENT SCIENCE Objectives: This course is intended to familiarise the students with the framework for the managers and leaders availbale for understanding and making decisions realting to issues related organiational structure, production operations, marketing, Human resource Management, product management and strategy. UNIT - I: Introduction to Management and Organisation: Concepts of Management and organization- nature, importance and Functions of Management, Systems Approach to Management - Taylor's Scientific Management Theory- Fayal's Principles of Management- Maslow's theory of Hierarchy of Human Needs- Douglas McGregor's Theory X and Theory Y - Hertzberg Two Factor Theory of Motivation - Leadership Styles, Social responsibilities of Management, Designing Organisational Structures: Basic concepts related to Organisation - Departmentation and Decentralisation, Types and Evaluation of mechanistic and organic structures of organisation and suitability. UNIT - II: Operations and Marketing Management: Principles and Types of Plant Layout-Methods of Production(Job, batch and Mass Production), Work Study - Basic procedure involved in Method Study and Work Measurement - Business Process Reengineering(BPR) - Statistical Quality Control: control charts for Variables and Attributes (simple Problems) and Acceptance Sampling, TQM, Six Sigma, Deming's contribution to quality, Objectives of Inventory control, EOQ, ABC Analysis, -
Manufacturing Execution Systems (MES)
Manufacturing Execution Systems (MES) Industry specific Requirements and Solutions ZVEI - German Electrical and Electronic Manufactures‘ Association Automation Division Lyoner Strasse 9 60528 Frankfurt am Main Germany Phone: + 49 (0)69 6302-292 Fax: + 49 (0)69 6302-319 E-mail: [email protected] www.zvei.org ISBN: 978-3-939265-23-8 CONTENTS Introduction and objectives IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII5 1. Market requirements and reasons for using MES IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII6 2. MES and normative standards (VDI 5600 / IEC 62264) IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII8 3. Classification of the process model according to IEC 62264 IIIIIIIIIIIIIIIIIIIIIIIIII 12 3.1 Resource Management IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII13 3.2 Definition Management IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII14 3.3 Detailed Scheduling IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII14 3.4 Dispatching IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII15 3.5 Execution Management IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII15 3.6 Data Collection IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII16 IMPRINT 3.7 Tracking IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII16 3.8 Analysis IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII17 Manufacturing Execution Systems (MES) 4. Typical MES modules and related terms IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII18 -
The Recent Trends in Production: 1
The Recent Trends in Production: 1. Flexibility: The ability to adapt quickly to changes in volumes of demand, in the product mix demanded, and in product design or delivery schedules, has become a major competitive strategy and a competitive advantage to the firms. This is sometimes called as agile (move quickly) manufacturing. 2. Total Quality Management: TQM approach has been adopted by many firms to achieve customer satisfaction by a never ending quest for improving the quality of goods and services. 3. Time Reduction: Reduction of manufacturing cycle time and speed to marker for a new product provide a competitive edge to a firm over other firms. When companies can provide products at the same price and quality, quicker delivery (short lead time) provide one firm competitive edge over the other. 4. Worker Involvement: The recent trend is to assign responsibility for decision making and problem solving to the lower levels in the organization. This is known as employee involvement and empowerment. Examples of employee’s empowerment are quality circle and use of work teams or quality improvement teams. 5. Business Process Re-engineering: BPR involves drastic measures or break-through improvements to improve the performance of a firm. It involves the concept of clean- state approach or starting from a scratch in redesigning in business processes. 6. Global Market Place: Globalization of business has compelled many manufacturing firms to give operations in many countries where they have certain economic advantage. This has resulted in a steep increase in the level of competition among manufacturing firms throughout the world. 7. -
JANNE HARJU PLANT INFORMATION MODELS for OPC UA: CASE COPPER REFINERY Master of Science Thesis
JANNE HARJU PLANT INFORMATION MODELS FOR OPC UA: CASE COPPER REFINERY Master of Science Thesis Examiner: Hannu Koivisto Examiner and topic approved in the Council meeting of Depart of Auto- mation Science and Engineering on 5.11.2014 i i TIIVISTELMÄ TAMPEREEN TEKNILLINEN YLIOPISTO Automaatiotekniikan koulutusohjelma HARJU, JANNE: PLANT INFORMATION MODELS FOR OPC UA: CASE COPPER REFINERY Diplomityö, 59 sivua Tammikuu 2015 Pääaine: Automaatio- ja informaatioverkot Tarkastaja: Professori Hannu Koivisto Avainsanat: OPC, UA, ISA-95, CAEX, mallinnus, ADI Isojen laitosten informaation rakenne on usein hankala ihmisen hahmottaa silloin, kun kaikki tieto on yhdessä listassa. Jotta laitoksen informaatiosta saadaan parempi koko- naiskuva, tarvitsee se mallintaa jollakin tekniikalla. Kun laitoksen mallintaa hierarkki- sesti, pystyy sen rakenteen hahmottamaan helpommin. Lisäksi, kun malliin saadaan tuotua mittaussignaaleja ja muuta mittauksiin ja muihin arvoihin liittyvää dataa, saadaan se tehokkaaseen käyttöön. Nykyään paljon käytetty klassinen OPC tuo datan käytettäväksi ylemmille lai- toksen tasoille. OPC tuo mittaukset pelkkänä listana, eikä se tuo mittausten välille mi- tään metatietoa. Tässä työssä on tarkoitus tutkia, miten mallintaa esimerkki laitokset käyttäen klassisen OPC:n seuraajaa OPC UA:ta. Työn tavoitteena on tutkia eri OPC UA:n mallinnustyökaluja, menetelmiä ja itse mallinnusta. Työssä tutustutaan OPC UA:n lisäksi ISA-95:n ja sen OPC UA- malliin ja miten tätä mallia pystyy käyttämään oikean laitoksen mallinnuksessa hyödyksi. ISA-95 lisäksi tutustutaan toiseen malliin nimeltä CAEX. CAEX on alun perin suunniteltu suunnitteludatan tallentamiseen stan- dardoidulla tavalla. CAEX:sta on olemassa myös tutkimuksia OPC UA:n kanssa käytet- täväksi ja tässä työssä tutustutaan, onko mallinnettavien tehtaiden kanssa mahdollista käyttää CAEX:ia hyödyksi. Virallista OPC UA CAEX- mallia ei ole vielä tosin julkais- tu. -
Open Tebi Thesis.Pdf
The Pennsylvania State University The Graduate School College of Engineering STUDY OF PROCESS IMPROVEMENT TOOLS IMPLEMENTED IN A CUSTOM ENGINEERED MANUFACTURING ENVIRONMENT A Thesis in Industrial Engineering by Tebi Mathew Cheeran © 2013 Tebi Mathew Cheeran Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science December 2013 The thesis of Tebi Mathew Cheeran was reviewed and approved* by the following: Robert Voigt Professor of Industrial and Manufacturing Engineering Thesis Co-adviser Christopher Saldana The Harold and Inge Marcus Career Assistant Professor Thesis Co-adviser Jeya Chandra Professor and Graduate Program Coordinator of Industrial and Manufacturing Engineering *Signatures are on file in the Graduate School. ii ABSTRACT The objective of this research project is to reduce the overall lead time for the manufacture and assembly of Blow Out Preventer stacks, having a highly customized design. The research project is executed for a multi-national company, specialized in the manufacture of mechanical components in the oil and gas industry. The work reviews some of the manufacturing strategies that are employed in today’s industries and tries to identify strategies that could be employed in a custom engineered, Make to Order environment. It then outlines some of the preliminary analysis done using the existing data from the facility. This analysis uses Six Sigma tools to develop an overview of the Blow Out Preventer production process and to identify key focus areas of the project. The preliminary analysis next focuses on the downstream final assembly process and identifies the assembly delays caused due to preassembly operations as the reason for long assembly lead time. -
Total Quality Management Course Code: POM-324 Author: Dr
Subject: Total Quality Management Course Code: POM-324 Author: Dr. Vijender Pal Saini Lesson No.: 1 Vetter: Dr. Sanjay Tiwari Concepts of Quality, Total Quality and Total Quality Management Structure 1.0 Objectives 1.1 Introduction 1.2 Concept of Quality 1.3 Dimensions of Quality 1.4 Application / Usage of Quality for General Public / Consumers 1.5 Application of Quality for Producers or Manufacturers 1.6 Factors affecting Quality 1.7 Quality Management 1.8 Total Quality Management 1.9 Characteristics / Nature of TQM 1.10 The TQM Practices Followed by Multinational Companies 1.11 Summary 1.12 Keywords 1.13 Self Assessment Questions 1.14 References / Suggested Readings 1 1.0 Objectives After going through this lesson, you will be able to: Understand the concept of Quality in day-to-day life and business. Differentiate between Quality and Quality Management Elaborate the concept of Total Quality Management 1.1 Introduction Quality is a buzz word in our lives. When the customer is in market, he or she is knowingly or unknowingly very cautious about the quality of product or service. Imagine the last buying of any product or service, e.g., mobile purchased last time. You must have enquired about various features like RAM, Operating System, Processor, Size, Body Colour, Cover, etc. If any of the features is not available, you might have suddenly changed the brand or have decided not to purchase it. Remember, how our mothers buy fruits, vegetables or grocery items. They are buying fresh and look-wise firm fruits, vegetable and groceries. Simultaneously, they are very conscious about the price of the fruits, vegetable and groceries. -
Industrial Engineering Industrial Engineering Is a Branch of Engineering Which Deals with the Optimization of Complex Processes Or Systems
Industrial engineering Industrial engineering is a branch of engineering which deals with the optimization of complex processes or systems. It is concerned with the development, improvement, and implementation of integrated systems of people, money, knowledge, information, equipment, energy, materials, analysis and synthesis, as well as the mathematical, physical and social sciences together with the principles and methods of engineering design to specify, predict, and evaluate the results to be obtained from such systems or processes.[1] While industrial engineering is a traditional and longstanding engineering discipline subject to (and eligible for) professional engineering licensure in most jurisdictions, its underlying concepts overlap considerably with certain business-oriented disciplines such as operations management. The various topics concerning industrial engineers include: accounting: the measurement, processing and communication of financial information about economic entities operations research, also known as management science: discipline that deals with the application of advanced analytical methods to help make better decisions operations management: an area of management concerned with overseeing, designing, and controlling the process of production and redesigning business operations in the production of goods or services. project management: is the process and activity of planning, organizing, motivating, and controlling resources, procedures and protocols to achieve specific goals in scientific or daily problems. -
Kpis As the Interface Between Scheduling and Control
Preprint, 11th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems June 6-8, 2016. NTNU, Trondheim, Norway KPIs as the interface between scheduling and control Margret Bauer1, Matthieu Lucke2,3, Charlotta Johnsson3, Iiro Harjunkoski2, Jan C. Schlake2 1University of the Witwatersrand, Johannesburg 2050, South Africa (email: [email protected]) 2ABB Corporate Research, Wallstadter Str. 59, 68526 Ladenburg, Germany (email:[email protected]) 3Department of Automatic Control, Lund University, 22100 Lund, Sweden (email [email protected]) Abstract: The integration of scheduling and control has been discussed in the past. While constructing an integrated plant model that may still seem out of reach, scheduling and control systems are increasingly more intertwined. We argue that they are in fact already integrated and give the example of two key performance indicators (KPIs) that are defined in the recent international standard ISO 22400. The focus of this study is on KPIs that consider both planned times and actual times. An amino acid production plant is used in the study, and the production is described from both the scheduling and the control perspective. To illustrate the integration, a schedule is computed containing the planned production times. Resulting measurements from the control system are analyzed for their actual production times using a proposed procedure that detects the start and end time of batches. Using KPIs as the interface between scheduling and control can be used as a strategy for maximizing the plant performance. The study focuses on the process industry. Keywords: Integration between scheduling and control, key performance indicator, distributed control system, planning and scheduling, batch process. -
Value Stream Mapping Adapted to High- Mix, Low-Volume Manufacturing Environments 2012:120
Value Stream Mapping adapted to High- Mix, Low-Volume Manufacturing Environments 2012:120 JUAN MANUEL ARAYA Master of Science Thesis Stockholm, Sweden 2011 VALUE STREAM MAPPING adapted to HIGH-MIX, LOW-VOLUME Manufacturing Environments Juan Manuel Araya Master of Science Thesis INDEK 2011:x KTH Industrial Engineering and Management Industrial Management SE-100 44 STOCKHOLM Examensarbete INDEK 2011:x {Rapporttitel} {Namn1} {Namn2} Godkänt Examinator Handledare 2011-mån-dag {Namn} {Namn} Uppdragsgivare Kontaktperson {Namn} {Namn} Sammanfattning Nyckelord Master of Science Thesis INDEK 2011:x {Title} {Name1} {Name2} Approved Examiner Supervisor 2011-month-day {Name} {Name} Commissioner Contact person {Name} {Name} Abstract This research work proposes a new methodology for implementing Value Stream Mapping, in processes that feature a High-Mix, Low-Volume product base. The opportunity for adapting the methodology singularly for these types of environments was identified because implementing Value Stream Mapping as proposed in Learning to See features several drawbacks when implemented in High-Mix, Low-Volume. Although Value Stream Mapping has been proven to enhance many types of processes, its advantages are shrunk if they are implemented in High- Mix, Low-Volume processes. High-Mix, Low-Volume processes are types of processes in which a high variety of finished goods are produced in relatively low amounts. The high variety of finished goods causes several complications for the implementation of flow. The difficulties that prevent the flow are the following: • The variance in the products: With hundreds, or sometimes thousands of possible finished goods, the number of products causes a non-repetitive process. • The variance in the routings: All of the products that are produced can have completely different process routings, or order of stations it has to visit.