Evaluating Lean Manufacturing Proposals Through Discrete Event Simulation – a Case Study at Alfa Laval
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School of Innovation, Design and Engineering Evaluating Lean Manufacturing Proposals through Discrete Event Simulation – A Case Study at Alfa Laval Master thesis work 30 credits, Advanced level Product and process development Production and Logistics Sönke Detjens Erik Flores Commissioned by: Alfa Laval Tutor (company): Rebecca Nilsson Tutor (university): Mats Jackson Examiner: Sabah Audo ABSTRACT In their strive for success in competitive markets companies often turn to Lean philosophy. However, for many companies Lean benefits are hard to substantialize especially when their ventures have met success through traditional manufacturing approaches. Traditional Lean tools analyze current situations or help Lean implementation. Therefore productions facilities require tools that enhance the evaluation of Lean proposals in such a way that decisions are supported by quantitative data and not only on a gut feeling. This thesis proposes how Discrete Event Simulation may be used as an evaluation tool in production process improvement to decide which proposal best suits Lean requirements. Theoretical and empirical studies were carried out. Literature review helped define the problem. A case study was performed at Alfa Laval to investigate through a holistic approach how and why did this tool provide a solution to the research questions. Case study analysis was substantiated with Discrete Event Simulation models for the evaluation of current and future state Lean proposals. Results of this study show that Discrete Event Simulation was not designed and does not function as a Lean specific tool. The use of Discrete Event Simulation in Lean assessment applications requires the organization to understand the principles of Lean and its desired effects. However, the use of traditional static Lean tools such as Value Stream Mapping and dynamic Discrete Event Simulation complement each other in a variety of ways. Discrete Event Simulation provides a unique condition to account for process variability and randomness. Both measurement of and reduction in variability through simulation provide insight to Lean implementation strategies. (Keywords: Lean, Manufacturing, Lean Tools, Discrete Event Simulation, Value Stream Mapping) ACKNOWLEDGEMENTS The authors would like to express their gratitude to Alfa Laval for the opportunity to develop this project. We would like to thank Rebecca Nilsson at the Lean Six Sigma Black Belt, Quality & Environment Department for her support on a professional and personal level. Special thanks to Jessica Bruch and Mats Jackson at MDH for their guidance and constructive criticism of our work. Lastly this thesis would not have been realized without the support of the Swedish winter and spring which kept us indoors. CONTENTS CONTENTS ...................................................................................................................................... i LIST OF FIGURES ..................................................................................................................... III LIST OF TABLES ....................................................................................................................... IV LIST OF ABBREVIATIONS ........................................................................................................ V 1. INTRODUCTION ................................................................................................................. 1 1.1 BACKGROUND ..................................................................................................................... 1 1.2 COMPANY INTRODUCTION ................................................................................................... 2 1.3 PROBLEM FORMULATION .................................................................................................... 3 1.4 AIM AND RESEARCH QUESTIONS ......................................................................................... 4 1.5 PROJECT LIMITATIONS ......................................................................................................... 4 2. RESEARCH METHODOLOGY ......................................................................................... 6 2.1 RESEARCH APPROACH ......................................................................................................... 6 2.2 RESEARCH METHOD ............................................................................................................ 6 2.3 LITERATURE REVIEW........................................................................................................... 7 2.4 DATA COLLECTION .............................................................................................................. 7 2.5 DATA ANALYSIS .................................................................................................................. 9 3. THEORETIC FRAMEWORK .......................................................................................... 10 3.1 LEAN AND ITS TOOLS ........................................................................................................ 10 3.1.1 Lean Development ............................................................................................... 10 3.1.2 Lean Implementation ............................................................................................ 11 3.1.3 Tools for Lean Implementation ........................................................................... 16 3.2 SIMULATION ...................................................................................................................... 21 3.2.1 Appliance of Simulation ....................................................................................... 21 3.2.2 Information that Simulation Provides ................................................................. 22 3.2.3 Systems and System Requirements .................................................................. 23 3.2.4 DES and ExtendSim............................................................................................. 24 3.2.5 Steps in Model-building ....................................................................................... 25 3.2.6 Data output validation .......................................................................................... 29 3.3 LEAN AND SIMULATION ..................................................................................................... 32 3.3.1 Reason for Fusion ................................................................................................ 32 3.3.2 DES complementing Lean ................................................................................... 33 4. EMPIRICS ........................................................................................................................... 35 4.1 ALFA LAVAL AND LEAN .................................................................................................... 35 4.2 THE PRODUCT.................................................................................................................... 37 4.3 PROCESS DESCRIPTIONS .................................................................................................... 38 4.3.1 Current Process .................................................................................................... 38 4.3.2 Current Process Analysis .................................................................................... 39 4.3.3 New Proposed Process ....................................................................................... 42 4.3.4 Need for Simulation .............................................................................................. 43 4.4 DISCRETE EVENT SIMULATION APPROACH........................................................................ 45 4.4.1 Model Data ............................................................................................................ 45 4.4.2 Current State Modeling ........................................................................................ 51 4.4.3 Future State Modeling .......................................................................................... 56 5. ANALYSIS ........................................................................................................................... 60 5.1 COMPARISON OF RESULTS ................................................................................................. 60 5.2 RESEARCH QUESTIONS ...................................................................................................... 63 5.2.1 What elements are required for DES to work as a tool to analyze different Lean proposals? ............................................................................................................................. 63 5.2.2 How do a dynamic tool such as DES and a static tool such as VSM complement each other? ............................................................................................................................ 68 i CONTENTS 5.2.3 What sort of information can DES provide to the analysis of different Lean proposals? ............................................................................................................................. 72 6. DISCUSSION AND CONCLUSIONS ............................................................................... 76 6.1 CASE STUDY RELATED RECOMMENDATIONS .................................................................... 76 6.2 RESEARCH FINDINGS ........................................................................................................