Synopses & Reviews
This proceedings volume of selected papers presented at the 1st Rapid Modelling Conference "Increasing Competitiveness - Tools and Mindset" gives a state-of-the-art overview of current research and new developments in the field of rapid modelling linked with lead time reduction. Rapid Modelling is generally based on queuing theory, but other mathematical modelling techniques are of interest, as are simulation models to facilitate the transfer of knowledge from theory to application, providing the theoretical foundations for successful lead time reduction. The interested reader (researcher as well as practitioner) should have a good overview of current activity in this field. Rapid Modelling for Increasing Competitiveness suggests that companies which are equipped for speed, with innovative processes, will outperform their slower competitors in many industries. Furthermore, this work also contributes to the scientific fields of operations management, production management, supply chain management, industrial engineering and operations research. The research papers presented in this book can be used to support the exchange of knowledge - between researchers, as well as practitioners - on the subject of increasing competitiveness through speed. Rapid Modelling for Increasing Competitiveness is supported by the EU Seventh Framework Programme - The People Programme - Industry-Academia Partnerships and Pathways Project (No. 217891) "How revolutionary queuing based modelling software helps keeping jobs in Europe. The creation of a lead time reduction software that increases industry competitiveness and supports academic research."
Synopsis
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."
About the Author
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.
Table of Contents
1. Managerial Decision Making and Lead Times: The Impact of Cognitive Illusions 2. Queueing Networks Modeling Software for Manufacturing 3. A Review of Decomposition Methods for Open Queueing Networks 4. Parsimonious Modeling and Forecasting of Time Series drifted by Autoregressive Noices 5. Forecast of the Traffic and Performance Evaluation of the BMT Container Terminal (Bejaia's Harbor) 6. A Dynamic Forecasting and Inventory Management Evaluation Approach 7. Performance Evaluation of Process Strategies Focussing on Lead Time Reduction Illustrated with an Existing Polymer Supply Chain 8. A Framework for Economic and Enivironmental Sustainability and Resilience of Supply Chains 9. An Integrative Approach to Inventory Control 10. Rapid Modeling of Express Line Systems for Improving Waiting Processes 11. Integrating Kanban Control with Advance Demand Information: Insights from an Analytical Model 12. Rapid Modelling in Manufacturing System Design Using Domain Specific Simulators 13. The Best of Both Worlds - Integrated Application of Analytic Methods and Simulation in Supply Chain Management 14. Rapid Modeling in a Lean Context 15. The Impact of Lean Management on Business Level Performance and Competitiveness 16. Reducing Service Process Lead-Time Through Inter-Organisational Process Coordination 17. Is There a Relationship Between VC Firm Business Process Flow Management and Investment Decisions? 18. What Causes Prolonger Lead-Times in Courts of Law? 19. Logistics Clusters - How Regional Value Chains Speed Up Global Supply Chains 20. Measuring the Effects of Improvements in Operations Management 21. Managing Demand Through the Enablers of Flexibility: The Impact of Forecasting and Process Flow Management 22. Threats of Sourcing Locally Without a Strategic Approach: Impacts on Lead Time Performances 23. Improving Lead Times Through Collaboration with Supply Chain Partners: Evidence from Australian Manufacturing Firms