Dynamic and Seamless Integration of Production, Logistics and Traffic (eBook)

Prof. Dr.-Ing. Eberhard Abele is head of the Institute of Production Management, Technology and Machine Tools at TU Darmstadt, Germany. Prof. Dr.-Ing. Manfred Boltze is head of the Department of Transport Planning and Traffic Engineering at TU Darmstadt, Germany. Prof. Dr. Dr. h.c. Hans-Christian Pfohl is head of Supply Chain and Network Management at TU Darmstadt, Germany.  

Contents 5
Interdisciplinary Research in Production, Logistics and Traffic: Introduction to Dynamo PLV and Overview of the Book 7
Introduction to Dynamo PLV 7
Overview of the Book 10
Chapter ``Interdisciplinary Decisions in Production, Logistics and Traffic and Transport´´ 11
Chapter ``The Interdisciplinary Decision Map´´ 11
Chapter ``Flexible Design of Lean Production Systems in Response to Fluctuations Due to Logistics and Traffic´´ 11
Chapter ``Simulation-Based Assessment of Lean Production Methods´´ 12
Chapter ``Revenue Sharing Between Production, Logistics and Traffic´´ 12
Chapter ``Supply Chain Risk Management in the Automotive Industry´´ 13
Chapter ``Temporal Shifts in Freight Traffic´´ 13
Chapter ``Freight Transport Demand Management´´ 14
Chapter ``Implications for Freight Transport Demand Modelling from Interdisciplinary Research´´ 14
References 15
Part I: Fundamentals of Interdisciplinary Research in Production, Logistics and Traffic 16
Interdisciplinary Decisions in Production, Logistics, and Traffic and Transport: Measures for Overcoming Barriers in Interdisc... 17
Introduction 17
Decision Theory and Interdisciplinary Decision-Making 18
Research Methodology and Empirical Data 20
Overcoming Barriers in Interdisciplinary Decision-Making 21
Identification of Barriers in Interdisciplinary Decision-Making 21
Measures to Facilitate Interdisciplinary Decision-Making 23
Development of a Framework for Characterizing Interrelations and Identifying Adequate Decision Support Solutions 25
Types of Decisions and Decision Interrelation Types in Production, Logistics, and Traffic 25
Decision Support Solutions and Their Applicability in Interdisciplinary Contexts 25
Derivation of Requirements for Interdisciplinary Decision Support 27
Information Management 27
Models 28
Methods 28
Communication 29
Exemplary Discussion of the Decision Support Requirements 29
Conclusion 30
Theoretical and Managerial Implications 30
Research Limitations and Future Research Directions 31
References 32
The Interdisciplinary Decision Map: A Reference Model for Production, Logistics and Traffic 35
Introduction 35
Understanding Interdisciplinary Decisions and Their Interrelations 37
Existing Reference Models in the Context of Production, Logistics and Traffic 37
Systems Theory and Interdisciplinary Decisions 38
Requirements for a Reference Model in the Context of Production, Logistics and Traffic 40
Methodology 40
IDM for Production, Logistics and Traffic 41
Elements of the IDM 41
Structural Framework 41
Modelling Language 43
Empirical Data: Decision Variables, Performance Indicators and Their Interrelations 44
Application Areas of the IDM 45
Impact Analysis and Checklists 45
Decision Support Development 46
Network Analysis 46
Using the IDM to Analyse Impacts of the Introduction of HGV Tolls 46
Status Quo of HGV Toll Implementation 46
Economic Impacts 47
Possible Reactions of Supply Chain Actors 47
Impact Analysis with the IDM 48
Conclusions and Outlook 49
References 49
Part II: Interdisciplinarity from a Domain Specific Perspective of Production, Logistics and Traffic 52
Flexible Design of Lean Production Systems in Response to Fluctuations Due to Logistics and Traffic 53
Introduction 53
Flexibility Requirements in Production due to Logistics and Traffic 54
Flexibility in Production: State of the Art 58
The Term ``Flexibility´´ in Manufacturing Contexts 58
Evaluation of Volume and Mix Flexibility in Manufacturing 59
Selected Evaluation Models for Volume Flexibility 59
Approach of Parker and Wirth (1999) 59
Approach of Das (1996) 60
Approach of Beamon (1999) 60
Selected Evaluation Models for Mix Flexibility 61
Approach of Das (1996) 61
Approach of Bateman et al. (1999) 62
Approach of Wahab (2005) 62
Selected Models for the Combined Evaluation of Volume and Mix Flexibility 62
Approach of Abele et al. (2008a) 63
Approach of Metternich et al. (2013a, b) 63
Summary and Review of Existing Approaches to Measure Volume and Mix Flexibility 64
Actions for Flexibility in Production 65
Technical Actions for Flexibility in Production 65
Overcapacity in Workstations/Machinery 65
Incremental Installation and Reduction of Manufacturing Equipment 66
Variation of the Level of Automation 66
Organizational Actions for Flexibility in Production 67
In- and Outsourcing of Work Content 67
Inventory Build-up and Reduction 67
Focusing on Bottlenecks and Continuous Expansion of Capacity and Capability 68
Human-Centred Actions for Flexibility in Production 68
Flexible Working Time Arrangements 68
Changes in Shift Models 68
Changes in the Number of Employees 69
Flexible Assignment of Employees to Workstations/Multidimensional Skills 69
Dealing with Flexibility in Lean Production Systems 70
Flexibility in Lean Assembly Systems 70
Volume Flexibility in Lean Assembly Systems 71
Mix Flexibility in Lean Assembly Systems 71
Mix and Volume Flexible Chaku-Chaku Cells in Lean Assembly Systems 73
Flexibility in Lean Machining Systems 73
Cellular Manufacturing as an Approach for Lean Machining Systems 75
Volume and Mix Flexibility in Machining with Cellular Manufacturing 77
Economic Aspects of Cellular Manufacturing 78
Summary and Outlook 80
References 81
Simulation-Based Assessment of Lean Production Methods: Approaches to Increase Volume and Variant Flexibility 85
Introduction 85
Approaches for the Description of Flexibility 86
Methodology and Research Approach 88
Production Environment 88
Simulation Modeling and System Constraints 89
Material Flow Model and Crucial Parameters 91
Customer Demand and Production Management 91
Logistics Concept 91
Assembly and Machining 92
Process Parameters of the Simulation 93
Identification of Flexibility Enhancing Lean Production Methods 94
Production leveling 95
Flexible Manufacturing System 95
Demand Managed Milk Run 96
Scenarios and Simulation Setup 96
Application to the Simulation Model 97
Production Leveling 97
Flexible Manufacturing System 99
Demand Managed Milk Run 101
Conclusions and Outlook 103
References 104
Revenue Sharing Between Production, Logistics and Traffic: An Experimental Analysis of the Actors in Distribution Logistics 107
Introduction 107
Research Background 109
Revenue-Sharing Contracts in Business Relationships 109
Laboratory Experiments and the Classic Investment Game 110
The Experiment Design 111
Experiment Procedure 112
Payment 114
Experimental Results 114
Conclusion 116
References 118
Supply Chain Risk Management in the Automotive Industry: Cross-Functional and Multi-tier Perspectives 121
Introduction 121
Theoretical Background and Research Methodology 123
Basics and Definitions 123
Research Methodology 125
Data Analysis 126
Major Findings 126
Supply Chain Risk Categories 128
Drivers of Supply Chain Risk 130
Actual Supply Chain Risk Management Gaps and Potential for Improvement 131
Practical Recommendations 135
The Three-Circle Model for Risk Identification and Assessment 135
Quantitative Approaches: Risk Measurement and Aggregation 138
Quantitative Impact Assessment 138
Modelling Joint Risk Factor Dynamics 140
Quantitative Risk Measurement 140
Aggregation of Supply Chain Risks 141
Risk Management Process: Multi-tier Supply Chain Risk Management Circle 142
Conclusion 143
Bibliography 145
Temporal Shifts in Freight Traffic: Estimating the Potential to Improve Traffic Quality on German Highways with Temporal Shift... 147
Introduction 147
Existing Measures to Influence the Time Choice 148
Methodology 150
Study Area and Counting Sites 150
Processing of Counting Site Data for Further Analysis 150
Conversion of Traffic Volumes into Passenger Car Units (PCU) 151
Determination of Levels of Service (LOS) with Respect to Traffic Flow 151
Generated Patterns 152
Results 153
Overlapping of Peak Hours and Overlapping of Periods with High Traffic Volumes 153
Temporal Shift of Traffic Volume Necessary to Achieve Level of Service D 156
Aggregation of HGV Traffic Patterns of Different Weekdays 157
Analysis of the Effects of the Truck Ban During Vacation Time 159
Conclusion 161
In Summary This Study Provides the Following Results 162
References 162
Freight Transport Demand Management: Influencing the Freight Transport Demand Within Traffic Management 164
Introduction 164
Relevant Stakeholders for Influencing the Freight Transport Demand 166
Transport Demand Management Within Traffic Management 168
Mobility Management to Influence the Demand in Passenger Traffic 168
Existing Approaches for Influencing the Freight Transport Demand 170
Requirements for a Concept to Influence Freight Transport Demand Within Traffic Management 171
The Concept of Freight Transport Demand Management 172
Definitions 172
Principles of Freight Transport Demand Management 173
Measures of Freight Transport Demand Management 175
Categorisation of Measures 175
Measures for Traffic Reduction 176
Measures for Spatial Shift of Traffic 177
Measures for Temporal Shift of Traffic 178
Measures for Modal Shift of Traffic 179
Measures for Traffic Control 179
Supportive Measures 180
Conclusions 180
References 182
Implications for Freight Transport Demand Modelling from Interdisciplinary Research: Developing a Concept for Modelling Freigh... 186
Introduction 186
Modelling in the Domain of Production, Logistics and Transport 187
Freight Transport and its Drivers 189
The German Automotive Industry from the Perspective of Freight Transport Demand Modelling 191
Potential Developments for the German Automotive Industry 195
Supply Chain Structure Effects as Drivers of Freight Transport Demand 196
Potential Data Sources for Freight Transport Demand Modelling 200
First Evidence for Supply Chain Structure Effects 202
Capturing Supply Chain Structure Effects in Freight Transport Demand Models 203
Conclusion and Outlook 205
References 206