Reiner Rapid Modelling for Increasing Competitiveness

Tools and Mindset
1. Auflage 2009
ISBN: 978-1-84882-748-6
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 310 Seiten

A Perspective on Two Decades of Rapid Modeling It is an honor for me to be asked to write a foreword to the Proceedings of the 1st Rapid Modeling Conference. In 1987, when I coined the term 'Rapid Modeling' to denote queuing modeling of manufacturing systems, I never imagined that two decades later there would be an international conference devoted to this topic! I am delighted to see that there will be around 40 presentations at the conference by leading researchers from aroundthe world, and about half of these presentationsare represented by written papers published in this book. I congratulate the conference organizers and program committee on the success of their efforts to hold the ?rst ever conference on Rapid Modeling. Attendees at this conferencemight?nd it interesting to learn about the history of the term Rapid Modeling in the context it is used here. During the fall of 1986 I was invited to a meeting at the Headquarters of the Society of Manufacturing Engineers (SME) in Dearborn, Michigan. By that time I had successfully demonstrated s- eral industry applications of queuing network models at leading manufacturers in the USA. Although in principle the use of queuing networks to model manufact- ing systems was well known in the OR/MS community and many papers had been published,the actual use of suchmodelsby manufacturingprofessionalswas almost nonexistent.

Gerald Reiner studied Business Administration in Vienna after an education in Industrial Engineering. In 2001 he received his Doctorate in Business Administration (Quality Management and Production Management) at the Vienna University of Economics and Business Administration, where he later received his Habilitation (venia legendi). Between 1999 and 2006 he was Assistant Professor at the Department of Production Management at the Vienna University of Economics and Business Administration. He served as visiting professor at Aston Business School (UK) in March 2006 and also at the University of Lausanne (Switzerland) from March 2007 to June 2007. Since February 2007 Gerald Reiner has been a full professor at the Enterprise Institute at the University of Neuchâtel, Switzerland. His research interests lie in the fields of supply chain management, quality management and operations management. He has published articles in International Journal of Production Economics, International Journal of Production Research, International Journal of Operations and Production Management, Operations Management Research, and other leading journals, as well as books and numerous book chapters.

Autoren/Hrsg.

Reiner, Gerald

Inhaltsverzeichnis

1;Foreword;5
2;Preface;9
3;Contents;12
4;List of Contributors;15
5;Part I Theory Pieces and Review;20
5.1;Chapter 1 Managerial Decision Making and Lead Times: The Impact of Cognitive Illusions;21
5.1.1;1.1 Introduction;22
5.1.2;1.2 Cognitive Illusions;22
5.1.3;1.3 Debiasing Techniques;28
5.1.4;1.4 Conclusions;30
5.1.5;References;30
5.2;Chapter 2 Queueing Networks Modeling Software for Manufacturing;33
5.2.1;2.1 Introduction;33
5.2.2;2.2 Queueing Networks Theory;34
5.2.3;2.3 Queueing Networks Software;35
5.2.4;2.4 Queueing Networks Software for Manufacturing;37
5.2.5;2.5 Further Remarks;38
5.2.6;References;39
5.3;Chapter 3 A Review of Decomposition Methods for Open Queueing Networks;42
5.3.1;3.1 Introduction;42
5.3.2;3.2 Jackson Networks;44
5.3.3;3.3 Generalised Jackson Networks;48
5.3.4;3.4 Other Classes of Networks;55
5.3.5;References;56
6;Part II Modelling and Simulation;60
6.1;Chapter 4 Parsimonious Modeling and Forecasting of Time Series drifted by Autoregressive Noise;61
6.1.1;4.1 Introduction;61
6.1.2;4.2 Extended Linear Growth Model for AR(p) Drifts;63
6.1.3;4.3 Estimation of the Parameters of the Extended Model;65
6.1.4;4.4 On Line Variance Learning;66
6.1.5;4.5 Forecast Function;66
6.1.6;4.6 Comments;67
6.1.7;References;67
6.2;Chapter 5 Forecast of the Traffic and Performance Evaluation of the BMT Container Terminal (Bejaia’s Harbor);68
6.2.1;5.1 Introduction;68
6.2.2;5.2 Park with Containers and Motion of the Containers;69
6.2.3;5.3 Mathematical Models;71
6.2.4;5.4 Calculation of the Forecasts;71
6.2.5;5.5 Performance Evaluation of the BMT Terminal;73
6.2.6;5.6 Variation of the Arrival Rate;77
6.2.7;5.7 Conclusion;78
6.3;Chapter 6 A Dynamic Forecasting and Inventory Management Evaluation Approach;80
6.3.1;6.1 Introduction;80
6.3.2;6.2 A Simple Supply Chain Model with Demand Forecasting;82
6.3.3;6.3 Model Verification and Validation;86
6.3.4;6.4 Empirical Data Analysis;88
6.3.5;6.5 Conclusion;90
6.3.6;References;91
6.4;Chapter 7 Performance Evaluation of Process Strategies Focussing on Lead Time Reduction Illustrated with an Existing Polymer Supply Chain;94
6.4.1;7.1 Introduction;94
6.4.2;7.2 Theoretical Background;95
6.4.3;7.3 Illustration of the Supply Chain;97
6.4.4;7.4 Conclusion;102
6.4.5;References;104
6.5;Chapter 8 A Framework for Economic and Environmental Sustainability and Resilience of Supply Chains;106
6.5.1;8.1 Introduction;107
6.5.2;8.2 Prevalent Logistics Trends: Cost Perspective;108
6.5.3;8.3 New Logistics Trends: Integrated Perspective;109
6.5.4;8.4 Transport-Focused Framework for Dual Sourcing;112
6.5.5;8.5 Single-Period Dual Sourcing Model Including Emission Costs;114
6.5.6;8.6 Summary;117
6.5.7;References;118
6.6;Chapter 9 An Integrative Approach To Inventory Control;120
6.6.1;9.1 Introduction;121
6.6.2;9.2 Framework for Integrated Inventory Control;123
6.6.3;9.3 Empirical Data;124
6.6.4;9.4 Simulation Model;127
6.6.5;9.5 Simulation Results;128
6.6.6;9.6 Discussion;129
6.6.7;9.7 Conclusions;131
6.6.8;References;132
6.7;Chapter 10 Rapid Modeling of Express Line Systems for ImprovingWaiting Processes;134
6.7.1;10.1 Introduction;134
6.7.2;10.2 Tools for Analyzing Express Line Systems;135
6.7.3;10.3 Objective Functions for Operating Express Line Systems;141
6.7.4;10.4 Optimization of the Waiting Process;142
6.7.5;10.5 Conclusions;143
6.7.6;References;144
6.8;Chapter 11 Integrating Kanban Control with Advance Demand Information: Insights from an Analytical Model;145
6.8.1;11.1 Introduction;145
6.8.2;11.2 Kanban Control System with ADI;146
6.8.3;11.3 Markov Chain Analysis;148
6.8.4;11.4 System Comparison;150
6.8.5;11.5 Conclusions and OngoingWork;154
6.8.6;References;155
6.9;Chapter 12 Rapid Modelling in Manufacturing System Design Using Domain Specific Simulators;156
6.9.1;12.1 Simulation in Manufacturing System Design;156
6.9.2;12.2 Rapid Modelling in Manufacturing Systems Design;158
6.9.3;12.3 Case Applications;160
6.9.4;12.4 Discussion of the Cases;164
6.9.5;12.5 Conclusions;165
6.9.6;References;166
6.10;Chapter 13 The Best of Both Worlds - Integrated Application of Analytic Methods and Simulation in Supply Chain Management;168
6.10.1;13.1 Combination of Analytic Methods and Simulation;168
6.10.2;13.2 Hybrid Models for Complex Supply Chains;170
6.10.3;13.3 Application in Supply Chain Management;171
6.10.4;13.4 Conclusion;174
6.11;Chapter 14 Rapid Modeling In A Lean Context;176
6.11.1;14.1 Introduction;176
6.11.2;14.2 The Quantification Of Lean;177
6.11.3;14.3 Conclusion;184
6.11.4;References;185
7;Part III Case Study and Action Research;187
7.1;Chapter 15 The Impact of Lean Management on Business Level Performance and Competitiveness;188
7.1.1;15.1 Introduction;189
7.1.2;15.2 The Research Framework;189
7.1.3;15.3 Methodology;194
7.1.4;15.4 Conclusion;205
7.1.5;References;206
7.2;Chapter 16 Reducing Service Process Lead-Time Through Inter-Organisational Process Coordination;210
7.2.1;16.1 Introduction;210
7.2.2;16.2 Research Objectives and Literature Review;211
7.2.3;16.3 Lead-Time Related Problem Analysis;213
7.2.4;16.4 Discussion;216
7.2.5;References;218
7.3;Chapter 17 Is There a Relationship Between VC Firm Business Process Flow Management and Investment Decisions?;219
7.3.1;17.1 Introduction;219
7.3.2;17.2 Research Method;220
7.3.3;17.3 Results;225
7.3.4;17.4 Discussion and Conclusion;226
7.3.5;References;228
7.4;Chapter 18 What Causes Prolonged Lead-Times in Courts of Law?;231
7.4.1;18.1 Introduction;231
7.4.2;18.2 Case Organizations;232
7.4.3;18.3 Process Improvement Projects and Data Collection;235
7.4.4;18.4 Analyzing the Factors Behind the Process Inefficiencies and Prolonged Lead-Times;236
7.4.5;18.5 Conclusions;239
7.4.6;References;240
7.5;Chapter 19 Logistics Clusters - How Regional Value Chains Speed Up Global Supply Chains;242
7.5.1;19.1 Introduction;242
7.5.2;19.2 Competitive Advantages through Clusters;244
7.5.3;19.3 Research Framework;246
7.5.4;19.4 Empirical Analysis;248
7.5.5;19.5 Further Research and Outlook;251
7.5.6;19.6 Appendix;251
7.5.7;References;252
8;Part IV Survey and Longitudinal Research;255
8.1;Chapter 20 Measuring the Effects of Improvements in Operations Management;256
8.1.1;20.1 Introduction;256
8.1.2;20.2 Literature Review;257
8.1.3;20.3 Research Questions, Sample Selection, and Methodology;260
8.1.4;20.4 Empirical Analysis, Results and Discussion;262
8.1.5;20.5 Summary and Conclusions;267
8.1.6;References;270
8.2;Chapter 21 Managing Demand Through the Enablers of Flexibility: The Impact of Forecasting and Process Flow Management;272
8.2.1;21.1 Introduction;272
8.2.2;21.2 The “Concept” of Flexibility;273
8.2.3;21.3 Objectives and Methodology;276
8.2.4;21.4 Empirical Analysis;277
8.2.5;21.5 Discussion;280
8.2.6;References;281
8.3;Chapter 22 Threats of Sourcing LocallyWithout a Strategic Approach: Impacts on Lead Time Performances;284
8.3.1;22.1 Introduction;284
8.3.2;22.2 Literature Review;285
8.3.3;22.3 Research Objectives and Methodology;287
8.3.4;22.4 Results;290
8.3.5;22.5 Discussion;294
8.3.6;22.6 Conclusion;296
8.3.7;References;296
8.4;Chapter 23 Improving Lead Times Through Collaboration With Supply Chain Partners: Evidence From Australian Manufacturing Firms;300
8.4.1;23.1 Introduction;300
8.4.2;23.2 Literature Review;301
8.4.3;23.3 Research Method;304
8.4.4;23.4 Data Analysis Procedures and Results;305
8.4.5;23.5 Discussion;309
8.4.6;23.6 Conclusion;310
8.4.7;References;310
9;Appendix A International Scientific Board;313
10;Appendix B Sponsors;314