Simulation for supply chain management:
"This book provides a detailed insight into the simulation approaches employed in the study of supply chain management and control. It begins by examining the types of simulation models (continuous simulation, discrete-event systems and simulation games) before moving on to the distribution lev...
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
London
ISTE [u.a.]
2008
|
| Schriftenreihe: | Control systems, robotics and manufacturing series
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Zusammenfassung: | "This book provides a detailed insight into the simulation approaches employed in the study of supply chain management and control. It begins by examining the types of simulation models (continuous simulation, discrete-event systems and simulation games) before moving on to the distribution levels of systems and models. It concludes with a thorough discussion of simulation products. Simulation methodologies and techniques are also covered throughout the text and case studies are included to highlight the pivotal role played by simulation in the decision-making processes of those working in this field."--BOOK JACKET. |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | XII, 346 S. Ill., graph. Darst. |
| ISBN: | 9781848210905 |
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| 300 | |a XII, 346 S. |b Ill., graph. Darst. | ||
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| 490 | 0 | |a Control systems, robotics and manufacturing series | |
| 500 | |a Includes bibliographical references and index | ||
| 520 | 1 | |a "This book provides a detailed insight into the simulation approaches employed in the study of supply chain management and control. It begins by examining the types of simulation models (continuous simulation, discrete-event systems and simulation games) before moving on to the distribution levels of systems and models. It concludes with a thorough discussion of simulation products. Simulation methodologies and techniques are also covered throughout the text and case studies are included to highlight the pivotal role played by simulation in the decision-making processes of those working in this field."--BOOK JACKET. | |
| 650 | 7 | |a Computersimulaties |2 gtt | |
| 650 | 7 | |a Ketenbeheer (logistiek) |2 gtt | |
| 650 | 7 | |a Logistique (organisation) - Simulation par ordinateur |2 ram | |
| 650 | 7 | |a Logistique (organisation) |2 ram | |
| 650 | 7 | |a Production - Gestion |2 ram | |
| 650 | 4 | |a Business logistics | |
| 650 | 4 | |a Production management | |
| 650 | 4 | |a Production management |x Computer simulation | |
| 650 | 4 | |a Business logistics |x Computer simulation | |
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Datensatz im Suchindex
| _version_ | 1804138057351299072 |
|---|---|
| adam_text | Titel: Simulation for supply chain management
Autor: Thierry, Caroline
Jahr: 2008
Table of Contents
Chapter 1. Supply Chain Management Simulation: An Overview........ 1
Caroline THIERRY, Gerard BEL and Andre THOMAS
1.1. Supply chain management.............................. 1
1.1.1. Supply chain viewpoints............................ 1
1.1.2. Supply chain management........................... 2
1.1.2.1. Supply chain processes: the integrated supply chain point of view 2
1.1.2.2. Dynamic behavior of supply chain management system...... 4
1.1.2.3. Supply chain processes: the collaborative supply chain
point of view..................................... 5
1.2. Supply chain management simulation....................... 5
1.2.1. Whyuse simulation for SCM?........................ 5
1.2.2. How can we use SCM simulation?...................... 7
1.3. Supply chain management simulation types................... 8
1.3.1. Production management models focus.................... 8
1.3.1.1. Time bucket models............................ 9
1.3.1.2. Starting time models........................... 10
1.3.2. Simulation types................................ 11
1.3.2.1. Size of the system............................ 11
1.3.2.2. Complexity of the production management system........ 11
1.3.2.3. Different types of models for SCM simulation........... 11
1.3.3. SCM simulation using continuous simulation approach........ 12
1.3.3.1. System dynamics............................. 12
1.3.3.2. Production management models/simulation models........ 13
1.3.4. SCM simulation using discrete-event approach............. 13
1.3.4.1. Time bucket-driven approach..................... 15
1.3.4.2. Event-driven approach......................... 18
1.3.5. Simulation of supply chain management using games......... 19
1.3.5.1. Games and simulation.......................... 19
1.3.5.2. Production management models/simulation models........ 20
vi Simulation for Supply Chain Management
1.4. Decision systems and simulation models (systems).............. 20
1.4.1. Models and system distribution....................... 20
1.4.2. Centralized simulation............................ 24
1.4.3. Multi-agent system decision simulation.................. 25
1.4.4. Simulation for product-driven systems................... 26
1.4.5. Model synchronization = HLA distributed simulation approaches . . 27
1.5. Simulation software................................ 29
1.6. Simulation methodology.............................. 29
1.6.1. Evaluation of simulation models...................... 29
1.6.2. Reduction of simulation models....................... 30
1.6.2.1. Reducing model literature review................... 30
1.6.2.2. The reducing model problem...................... 31
1.6.2.3. Another state reduction using the bottleneck notion........ 32
1.7. Conclusion...................................... 34
1.8. Bibliography..................................... 35
Chapter 2. Continuous Simulation for SCM.................... 37
Daniel THIEL and Vo Thi Le HOA
2.1. System dynamics models for SCM....................... 37
2.1.1. Complexity in supply chain logistics.................... 37
2.1.2. Cybernetics and feedback concept..................... 38
2.1.3. Basic principles of system dynamics.................... 39
2.1.3.1. Forrester s theory............................. 39
2.1.3.2. Simulation techniques.......................... 42
2.1.4. How can we represent the supply chain decision system?....... 44
2.1.5. Literature review................................ 46
2.2. Application: recent research into the bullwhip effect............. 48
2.2.1. Bullwhip effect in supply chains...................... 48
2.2.1.1. Bullwhip effect definition........................ 48
2.2.1.2. Supply chain perturbations....................... 48
2.2.1.3. Bullwhip effect causes......................... 48
2.2.1.4. Bullwhip effect reduction solutions.................. 49
2.2.2. Bullwhip effect modeling.......................... 50
2.2.2.1. Example of a BE diffusion model................... 50
2.2.2.2. BE system dynamics models...................... 52
2.2.2.3. BE multi-agent models......................... 57
2.3. Conclusion...................................... 59
2.4. Bibliography..................................... 59
2.5. Appendix 1...................................... 65
Table of Contents vii
Chapter 3. Discrete-event Simulation for Supply Chain Management. ... 69
Valerie BOTTA-GENOULAZ, Jacques LAMOTHE, Florence PICARD, Fouad RIANE
and Anthony VALLA
3.1. Discrete-event simulation and supply chain.................. 69
3.1.1. Introduction................................... 69
3.1.2. Event-driven and time bucket-driven simulation for supply chains. . 70
3.2. Discrete-event simulation for supply chain redesign............. 73
3.2.1. Problem definition............................... 73
3.2.2. Problem statement............................... 74
3.2.3. Decision aid approach............................ 75
3.2.4. Models of the decision aid approach.................... 76
3.2.5. Discrete-event simulation model...................... 77
3.2.5.1. Resources................................. 77
3.2.5.2. Simulated processes........................... 77
3.2.5.3. Simulation and decision-making.................... 79
3.2.5.4. Performance indicators......................... 80
3.2.6. Illustrative application............................ 80
3.3. Discrete-event simulation for cooperation process risk analysis...... 83
3.3.1. Context of the study.............................. 83
3.3.2. The simulator s principles.......................... 84
3.3.3. Example of application............................ 87
3.4. Discrete-event simulation for business process reengineering........ 91
3.4.1. Methodology.................................. 91
3.4.1.1. Modeling................................. 92
3.4.1.2. Simulation and diagnosis........................ 93
3.4.1.3. Evaluation of different solutions.................... 93
3.4.2. Application................................... 94
3.4.2.1. Description of the business process.................. 94
3.4.2.2. Application of the modeling stage................... 95
3.4.2.3. Application of the simulation and diagnosis stage......... 95
3.4.2.4. Evaluation of different solutions in the third stage......... 97
3.4.3. Discussion................................... 98
3.5. Conclusion...................................... 99
3.6. Bibliography..................................... 99
Chapter 4. Simulation Games.............................. 103
Thierry MOYAUX, Eric BALLOT, Michel GREIF and Bertrand SIMON
4.1. Introduction..................................... 103
4.2. Literature review.................................. 104
4.2.1. Board games.................................. 106
4.2.1.1. The Beer Game.............................. 1Q6
4.2.1.2. Derivatives of the Beer Game..................... 108
viii Simulation for Supply Chain Management
4.2.1.3. The Trust and Tracing Game...................... Ill
4.2.1.4. The Mortgage Service Game...................... Ill
4.2.1.5. Legostics Management......................... Ill
4.2.1.6. Risk pooling................................ 112
4.2.2. Sophisticated games.............................. 112
4.2.2.1. Trading Agent Competition-Supply Chain Management .... 112
4.2.2.2. Chain Game for distributed trading and negotiation........ 113
4.2.2.3. Business Network Lab......................... 114
4.2.2.4. SIMBU................................... 114
4.3. Theories about the usage of games........................114
4.3.1. Games as a booster for learners?......................115
4.3.1.1. Backgrounds...............................115
4.3.1.2. Evaluation.................................116
4.3.2. Games as a research field for managerial behavior...........117
4.3.2.1. The role of the human factor in replenishment or inventory
decisions.......................................117
4.3.2.2. Why choose games to conduct supply chain research?......117
4.3.2.3. Testing hypothesis on manager behavior...............117
4.4. Examples of implementation methodologies and obtained results.....119
4.4.1. Kanban game in academic institutions...................121
4.4.2. A field for experimentation.........................123
4.5. Conclusion......................................123
4.6. Bibliography.....................................123
Chapter 5. Centralized Approaches for Supply Chain Simulation: Issues and
Applications.........................................129
Lyes BENYOUCEF, Vipul JAIN and Patrick CHARPENTIER
5.1. Introduction..................................... 129
5.2. Supply chain centralized simulation - a literature review.......... 130
5.3. Supply chain simulation using centralized approaches............ 134
5.4. Some industrial and practical applications................... 134
5.4.1. Production —distribution network design in automotive industry. . . 134
5.4.1.1. Network description........................... 135
5.4.1.2. Make-to-Stock and Make-to-Order strategies............ 136
5.4.1.3. The simulation model.......................... 136
5.4.1.4. Optimization variables......................... 138
5.4.1.5. Optimization specifications....................... 139
5.4.1.6. Experimental results and analyses................... 139
5.4.2. Supplier selection problem in textile industry.............. 141
5.4.2.1. Supply chain description........................141
5.4.2.2. The simulation-optimization model..................143
5.4.2.3. Genetic representation and operations................143
Table of Contents ix
5.4.2.4. Discrete-event simulation model................... 144
5.4.2.5. Experimental results and analyses................... 145
5.4.3. Another practical example from the automotive industry........ 147
5.4.3.1. Supply chain description........................ 147
5.4.3.2. From the generic model of a supply flow to its simulation .... 149
5.4.3.3. Illustrative example........................... 152
5.5. Conclusions and perspectives........................... 153
5.6. Bibliography..................................... 154
Chapter 6. The Interest of Agents for Supply Chain Simulation....... 159
Thibaud MONTEIRO, Didier ANCIAUX, Bernard ESPINASSE, Alain FERRARINI,
Olivier LABARTHE and Daniel ROY
6.1. Decision problems in enterprise networks................... 159
6.2. State of the art: modeling and simulation of supply chains with agents . . 161
6.2.1. Introduction to the agent and MAS...................... 161
6.2.1.1. Agent definition and typology...................... 162
6.2.1.2. MAS...................................... 164
6.2.2. Supply chain simulation with agents..................... 168
6.2.2.1. Interests of the agent approach...................... 168
6.2.2.2. Review of works on agent-based supply chain modeling
and simulation..................................... 171
6.3. Conclusion and summary of the projects.................... 181
6.4. Bibliography..................................... 183
Chapter 7. Agent-based Simulation of Business Network Planning and
Coordination Systems................................... 189
Thibaud MONTEIRO, Didier ANCIAUX, Sophie D AMOURS, Bernard ESPINASSE,
Alain FERRARINI, Olivier LABARTHE and Daniel ROY
7.1. Decision system in a supply chain........................ 189
7.2. Decision-making tools to supply chain control................ 190
7.2.1. Distributed planning in supply chain.................... 191
7.2.1.1. Multi-agent architecture.......................... 191
7.2.1.2. Planning the supply chain......................... 192
7.2.2. Confirmed order management in a stochastic environment........ 197
7.2.2.1. Decision problem.............................. 197
7.2.2.2. Decision process for new order integration............... 198
7.2.3. Experimental agent-based platform for tactical planning in the softwood
lumber industry.................................... 200
7.3. Simulation tools to design supply chain planning and
coordination systems................................... 203
7.3.1. Order management evaluation......................... 203
x Simulation for Supply Chain Management
7.3.2. Performance evaluation of various coordination policies according
to the location of the decoupling point........................206
7.3.3. Design of cooperation mechanism.......................212
7.3.3.1. Example of simulation for multi-negotiation parameter.......213
7.3.4. SPEE........................................215
7.4. Bibliography.....................................218
Chapter 8. Simulation for Product-driven Systems................221
Andre THOMAS, Pierre CASTAGNA, Remi PANNEQUIN, Thomas KLEIN,
Hind EL HAOUZI, Pascal BLANC and Olivier CARDIN
8.1. Introduction.....................................221
8.2. Control architectures of manufacturing systems................222
8.2.1. Hierarchical control architectures...................... 222
8.2.2. Heterarchical control architectures..................... 223
8.2.3. Product-driven architectures......................... 224
8.3. Validation with simulation in HMS or product-driven systems....... 227
8.3.1. Concept of emulation.............................228
8.3.2. Simulation modeling with emulator and control system........229
8.3.2.1. Emulation model............................. 229
8.3.2.2. Control model............................... 230
8.4. Simulation: a computer-aided tool for product-driven systems....... 232
8.5. Industrial applications............................... 234
8.5.1. Furniture company case study........................234
8.5.1.1. Context...................................234
8.5.1.2. Proposed architecture..........................236
8.5.2. Multi-line synchronization..........................239
8.5.2.1. Industrial context............................. 239
8.5.2.2. System architecture at Trane...................... 240
8.5.2.3. Limits and perspectives......................... 244
8.5.3. AGP case study................................ 245
8.5.3.1. Context................................... 245
8.5.3.2. Proposed architecture.......................... 246
8.5.3.3. Evaluation of the control by simulation............... 251
8.6. Conclusion...................................... 252
8.7. Bibliography..................................... 253
Chapter 9. HLA Distributed Simulation Approaches for Supply Chains . . 257
Fouzia OUNNAR, Bernard ARCHIMEDE, Philippe CHARBONNAUD
and Patrick PUJO
9.1. Introduction.....................................257
9.2. Modeling and discrete-event simulation....................259
9.2.1. Specification using DEVS and SIMBA..................259
Table of Contents xi
9.2.2. Model interoperability............................260
9.2.3. Model interaction protocols.........................261
9.3. Self-organized control of supply chain networks...............264
9.3.1. Problematics.................................. 264
9.3.2. Choice of a decision structure........................ 265
9.3.3. Holonic approach for self-organized control of logistic network . . . 266
9.3.4. DEVS-EPA modeling and distributed simulation in
HLA environment................................... 269
9.3.5. Ranking and evaluation of the supplier process............. 272
9.3.6. Analysis of the simulation results: manufacturing of cosmetic
products by an enterprise network......................... 274
9.4. Reactive control by evaluation of multi-site plans............... 276
9.4.1. Problem statement...............................276
9.4.2. Development method and tools of multi-site plans...........277
9.4.3. Conceptual multi-agent SCEP model...................278
9.4.4. Principle of deployment in the SCEP network..............281
9.4.5. Development process of multi-site plans.................283
9.4.6. Evaluation method and tools of multi-site plans.............283
9.4.7. Evaluation by distributed simulation, interest and limits........288
9.5. Conclusion......................................289
9.6. Bibliography.....................................290
Chapter 10. Software Tools for Simulation.....................295
Franck FONTANILI, Pierre CASTAGNA and Bernard YANNOU
10.1. Short history of the tools for simulation in industrial engineering .... 295
10.2. Typology of the simulation tools for the supply chain...........296
10.2.1. General classification............................297
10.2.2. Classification according to the versatility and the facility of use. . . 298
10.2.3. Classification of discrete-event simulation according to the life-
cycle of the process..................................299
10.2.4. Specific classification for SCM......................301
10.2.5. The system dynamics software......................301
10.3. Key points of the construction of a simulation model............304
10.3.1. Stage of modeling the actions of a process...............304
10.3.2. Stage of describing the laws and rules..................305
10.3.3. Logic elements................................305
10.3.4. Horizon of simulation............................306
10.4. Limits and objectives of simulation tools...................307
10.4.1. What they can do............................... 307
10.4.2. What they cannot do............................. 307
10.5. Methodology of a simulation project...................... 308
10.5.1. Step 1: problem analysis.......................... 3°9
xii Simulation for Supply Chain Management
10.5.2. Step 2: modeling and programming.................... 310
10.5.3. Step 3: simulations.............................. 313
10.5.4. Step 4: report/ratio and conclusions.................... 313
10.6. Possibilities of coupling............................. 314
10.6.1. Input/output data analysis.......................... 314
10.6.2. Inputs/outputs via spreadsheet or database................ 315
10.6.3. Control simulator from an external client................ 316
10.6.4. Coupling with the real process (online simulation)........... 317
10.7. Main functionalities and criteria of selection of a tool........... 318
10.8. Classification of the commercial tools..................... 319
10.8.1. Offer highlights................................ 319
10.8.2. General presentation of three software tools............... 320
10.8.2.1. Arena™................................. 320
10.8.2.2. Witness™................................ 320
10.8.2.3. Quest™.................................. 321
10.9. Example of modeling with three tools..................... 321
10.9.1. Description of the process and knowledge model........... 321
10.9.2. Modeling with Arena............................ 322
10.9.3. Modeling and simulation with Witness.................. 326
10.9.4. Modeling with Quest............................ 331
10.9.5. Example of modeling of a total logistic chain.............. 335
10.10. Useful links.................................... 335
10.11. Bibliography................................... 336
List of Authors....................................... 339
Index............................................. 345
|
| adam_txt |
Titel: Simulation for supply chain management
Autor: Thierry, Caroline
Jahr: 2008
Table of Contents
Chapter 1. Supply Chain Management Simulation: An Overview. 1
Caroline THIERRY, Gerard BEL and Andre THOMAS
1.1. Supply chain management. 1
1.1.1. Supply chain viewpoints. 1
1.1.2. Supply chain management. 2
1.1.2.1. Supply chain processes: the integrated supply chain point of view 2
1.1.2.2. Dynamic behavior of supply chain management system. 4
1.1.2.3. Supply chain processes: the collaborative supply chain
point of view. 5
1.2. Supply chain management simulation. 5
1.2.1. Whyuse simulation for SCM?. 5
1.2.2. How can we use SCM simulation?. 7
1.3. Supply chain management simulation types. 8
1.3.1. Production management models focus. 8
1.3.1.1. Time bucket models. 9
1.3.1.2. Starting time models. 10
1.3.2. Simulation types. 11
1.3.2.1. Size of the system. 11
1.3.2.2. Complexity of the production management system. 11
1.3.2.3. Different types of models for SCM simulation. 11
1.3.3. SCM simulation using continuous simulation approach. 12
1.3.3.1. System dynamics. 12
1.3.3.2. Production management models/simulation models. 13
1.3.4. SCM simulation using discrete-event approach. 13
1.3.4.1. Time bucket-driven approach. 15
1.3.4.2. Event-driven approach. 18
1.3.5. Simulation of supply chain management using games. 19
1.3.5.1. Games and simulation. 19
1.3.5.2. Production management models/simulation models. 20
vi Simulation for Supply Chain Management
1.4. Decision systems and simulation models (systems). 20
1.4.1. Models and system distribution. 20
1.4.2. Centralized simulation. 24
1.4.3. Multi-agent system decision simulation. 25
1.4.4. Simulation for product-driven systems. 26
1.4.5. Model synchronization = HLA distributed simulation approaches . . 27
1.5. Simulation software. 29
1.6. Simulation methodology. 29
1.6.1. Evaluation of simulation models. 29
1.6.2. Reduction of simulation models. 30
1.6.2.1. Reducing model literature review. 30
1.6.2.2. The reducing model problem. 31
1.6.2.3. Another state reduction using the bottleneck notion. 32
1.7. Conclusion. 34
1.8. Bibliography. 35
Chapter 2. Continuous Simulation for SCM. 37
Daniel THIEL and Vo Thi Le HOA
2.1. System dynamics models for SCM. 37
2.1.1. Complexity in supply chain logistics. 37
2.1.2. Cybernetics and feedback concept. 38
2.1.3. Basic principles of system dynamics. 39
2.1.3.1. Forrester's theory. 39
2.1.3.2. Simulation techniques. 42
2.1.4. How can we represent the supply chain decision system?. 44
2.1.5. Literature review. 46
2.2. Application: recent research into the bullwhip effect. 48
2.2.1. Bullwhip effect in supply chains. 48
2.2.1.1. Bullwhip effect definition. 48
2.2.1.2. Supply chain perturbations. 48
2.2.1.3. Bullwhip effect causes. 48
2.2.1.4. Bullwhip effect reduction solutions. 49
2.2.2. Bullwhip effect modeling. 50
2.2.2.1. Example of a BE diffusion model. 50
2.2.2.2. BE system dynamics models. 52
2.2.2.3. BE multi-agent models. 57
2.3. Conclusion. 59
2.4. Bibliography. 59
2.5. Appendix 1. 65
Table of Contents vii
Chapter 3. Discrete-event Simulation for Supply Chain Management. . 69
Valerie BOTTA-GENOULAZ, Jacques LAMOTHE, Florence PICARD, Fouad RIANE
and Anthony VALLA
3.1. Discrete-event simulation and supply chain. 69
3.1.1. Introduction. 69
3.1.2. Event-driven and time bucket-driven simulation for supply chains. . 70
3.2. Discrete-event simulation for supply chain redesign. 73
3.2.1. Problem definition. 73
3.2.2. Problem statement. 74
3.2.3. Decision aid approach. 75
3.2.4. Models of the decision aid approach. 76
3.2.5. Discrete-event simulation model. 77
3.2.5.1. Resources. 77
3.2.5.2. Simulated processes. 77
3.2.5.3. Simulation and decision-making. 79
3.2.5.4. Performance indicators. 80
3.2.6. Illustrative application. 80
3.3. Discrete-event simulation for cooperation process risk analysis. 83
3.3.1. Context of the study. 83
3.3.2. The simulator's principles. 84
3.3.3. Example of application. 87
3.4. Discrete-event simulation for business process reengineering. 91
3.4.1. Methodology. 91
3.4.1.1. Modeling. 92
3.4.1.2. Simulation and diagnosis. 93
3.4.1.3. Evaluation of different solutions. 93
3.4.2. Application. 94
3.4.2.1. Description of the business process. 94
3.4.2.2. Application of the modeling stage. 95
3.4.2.3. Application of the simulation and diagnosis stage. 95
3.4.2.4. Evaluation of different solutions in the third stage. 97
3.4.3. Discussion. 98
3.5. Conclusion. 99
3.6. Bibliography. 99
Chapter 4. Simulation Games. 103
Thierry MOYAUX, Eric BALLOT, Michel GREIF and Bertrand SIMON
4.1. Introduction. 103
4.2. Literature review. 104
4.2.1. Board games. 106
4.2.1.1. The Beer Game. 1Q6
4.2.1.2. Derivatives of the Beer Game. 108
viii Simulation for Supply Chain Management
4.2.1.3. The Trust and Tracing Game. Ill
4.2.1.4. The Mortgage Service Game. Ill
4.2.1.5. Legostics Management. Ill
4.2.1.6. Risk pooling. 112
4.2.2. Sophisticated games. 112
4.2.2.1. Trading Agent Competition-Supply Chain Management . 112
4.2.2.2. Chain Game for distributed trading and negotiation. 113
4.2.2.3. Business Network Lab. 114
4.2.2.4. SIMBU. 114
4.3. Theories about the usage of games.114
4.3.1. Games as a booster for learners?.115
4.3.1.1. Backgrounds.115
4.3.1.2. Evaluation.116
4.3.2. Games as a research field for managerial behavior.117
4.3.2.1. The role of the "human factor" in replenishment or inventory
decisions.117
4.3.2.2. Why choose games to conduct supply chain research?.117
4.3.2.3. Testing hypothesis on manager behavior.117
4.4. Examples of implementation methodologies and obtained results.119
4.4.1. Kanban game in academic institutions.121
4.4.2. A field for experimentation.123
4.5. Conclusion.123
4.6. Bibliography.123
Chapter 5. Centralized Approaches for Supply Chain Simulation: Issues and
Applications.129
Lyes BENYOUCEF, Vipul JAIN and Patrick CHARPENTIER
5.1. Introduction. 129
5.2. Supply chain centralized simulation - a literature review. 130
5.3. Supply chain simulation using centralized approaches. 134
5.4. Some industrial and practical applications. 134
5.4.1. Production —distribution network design in automotive industry. . . 134
5.4.1.1. Network description. 135
5.4.1.2. Make-to-Stock and Make-to-Order strategies. 136
5.4.1.3. The simulation model. 136
5.4.1.4. Optimization variables. 138
5.4.1.5. Optimization specifications. 139
5.4.1.6. Experimental results and analyses. 139
5.4.2. Supplier selection problem in textile industry. 141
5.4.2.1. Supply chain description.141
5.4.2.2. The simulation-optimization model.143
5.4.2.3. Genetic representation and operations.143
Table of Contents ix
5.4.2.4. Discrete-event simulation model. 144
5.4.2.5. Experimental results and analyses. 145
5.4.3. Another practical example from the automotive industry. 147
5.4.3.1. Supply chain description. 147
5.4.3.2. From the generic model of a supply flow to its simulation . 149
5.4.3.3. Illustrative example. 152
5.5. Conclusions and perspectives. 153
5.6. Bibliography. 154
Chapter 6. The Interest of Agents for Supply Chain Simulation. 159
Thibaud MONTEIRO, Didier ANCIAUX, Bernard ESPINASSE, Alain FERRARINI,
Olivier LABARTHE and Daniel ROY
6.1. Decision problems in enterprise networks. 159
6.2. State of the art: modeling and simulation of supply chains with agents . . 161
6.2.1. Introduction to the agent and MAS. 161
6.2.1.1. Agent definition and typology. 162
6.2.1.2. MAS. 164
6.2.2. Supply chain simulation with agents. 168
6.2.2.1. Interests of the agent approach. 168
6.2.2.2. Review of works on agent-based supply chain modeling
and simulation. 171
6.3. Conclusion and summary of the projects. 181
6.4. Bibliography. 183
Chapter 7. Agent-based Simulation of Business Network Planning and
Coordination Systems. 189
Thibaud MONTEIRO, Didier ANCIAUX, Sophie D'AMOURS, Bernard ESPINASSE,
Alain FERRARINI, Olivier LABARTHE and Daniel ROY
7.1. Decision system in a supply chain. 189
7.2. Decision-making tools to supply chain control. 190
7.2.1. Distributed planning in supply chain. 191
7.2.1.1. Multi-agent architecture. 191
7.2.1.2. Planning the supply chain. 192
7.2.2. Confirmed order management in a stochastic environment. 197
7.2.2.1. Decision problem. 197
7.2.2.2. Decision process for new order integration. 198
7.2.3. Experimental agent-based platform for tactical planning in the softwood
lumber industry. 200
7.3. Simulation tools to design supply chain planning and
coordination systems. 203
7.3.1. Order management evaluation. 203
x Simulation for Supply Chain Management
7.3.2. Performance evaluation of various coordination policies according
to the location of the decoupling point.206
7.3.3. Design of cooperation mechanism.212
7.3.3.1. Example of simulation for multi-negotiation parameter.213
7.3.4. SPEE.215
7.4. Bibliography.218
Chapter 8. Simulation for Product-driven Systems.221
Andre THOMAS, Pierre CASTAGNA, Remi PANNEQUIN, Thomas KLEIN,
Hind EL HAOUZI, Pascal BLANC and Olivier CARDIN
8.1. Introduction.221
8.2. Control architectures of manufacturing systems.222
8.2.1. Hierarchical control architectures. 222
8.2.2. Heterarchical control architectures. 223
8.2.3. Product-driven architectures. 224
8.3. Validation with simulation in HMS or product-driven systems. 227
8.3.1. Concept of emulation.228
8.3.2. Simulation modeling with emulator and control system.229
8.3.2.1. Emulation model. 229
8.3.2.2. Control model. 230
8.4. Simulation: a computer-aided tool for product-driven systems. 232
8.5. Industrial applications. 234
8.5.1. Furniture company case study.234
8.5.1.1. Context.234
8.5.1.2. Proposed architecture.236
8.5.2. Multi-line synchronization.239
8.5.2.1. Industrial context. 239
8.5.2.2. System architecture at Trane. 240
8.5.2.3. Limits and perspectives. 244
8.5.3. AGP case study. 245
8.5.3.1. Context. 245
8.5.3.2. Proposed architecture. 246
8.5.3.3. Evaluation of the control by simulation. 251
8.6. Conclusion. 252
8.7. Bibliography. 253
Chapter 9. HLA Distributed Simulation Approaches for Supply Chains . . 257
Fouzia OUNNAR, Bernard ARCHIMEDE, Philippe CHARBONNAUD
and Patrick PUJO
9.1. Introduction.257
9.2. Modeling and discrete-event simulation.259
9.2.1. Specification using DEVS and SIMBA.259
Table of Contents xi
9.2.2. Model interoperability.260
9.2.3. Model interaction protocols.261
9.3. Self-organized control of supply chain networks.264
9.3.1. Problematics. 264
9.3.2. Choice of a decision structure. 265
9.3.3. Holonic approach for self-organized control of logistic network . . . 266
9.3.4. DEVS-EPA modeling and distributed simulation in
HLA environment. 269
9.3.5. Ranking and evaluation of the supplier process. 272
9.3.6. Analysis of the simulation results: manufacturing of cosmetic
products by an enterprise network. 274
9.4. Reactive control by evaluation of multi-site plans. 276
9.4.1. Problem statement.276
9.4.2. Development method and tools of multi-site plans.277
9.4.3. Conceptual multi-agent SCEP model.278
9.4.4. Principle of deployment in the SCEP network.281
9.4.5. Development process of multi-site plans.283
9.4.6. Evaluation method and tools of multi-site plans.283
9.4.7. Evaluation by distributed simulation, interest and limits.288
9.5. Conclusion.289
9.6. Bibliography.290
Chapter 10. Software Tools for Simulation.295
Franck FONTANILI, Pierre CASTAGNA and Bernard YANNOU
10.1. Short history of the tools for simulation in industrial engineering . 295
10.2. Typology of the simulation tools for the supply chain.296
10.2.1. General classification.297
10.2.2. Classification according to the versatility and the facility of use. . . 298
10.2.3. Classification of discrete-event simulation according to the life-
cycle of the process.299
10.2.4. Specific classification for SCM.301
10.2.5. The system dynamics software.301
10.3. Key points of the construction of a simulation model.304
10.3.1. Stage of modeling the actions of a process.304
10.3.2. Stage of describing the laws and rules.305
10.3.3. Logic elements.305
10.3.4. Horizon of simulation.306
10.4. Limits and objectives of simulation tools.307
10.4.1. What they can do. 307
10.4.2. What they cannot do. 307
10.5. Methodology of a simulation project. 308
10.5.1. Step 1: problem analysis. 3°9
xii Simulation for Supply Chain Management
10.5.2. Step 2: modeling and programming. 310
10.5.3. Step 3: simulations. 313
10.5.4. Step 4: report/ratio and conclusions. 313
10.6. Possibilities of coupling. 314
10.6.1. Input/output data analysis. 314
10.6.2. Inputs/outputs via spreadsheet or database. 315
10.6.3. Control simulator from an external client. 316
10.6.4. Coupling with the real process (online simulation). 317
10.7. Main functionalities and criteria of selection of a tool. 318
10.8. Classification of the commercial tools. 319
10.8.1. Offer highlights. 319
10.8.2. General presentation of three software tools. 320
10.8.2.1. Arena™. 320
10.8.2.2. Witness™. 320
10.8.2.3. Quest™. 321
10.9. Example of modeling with three tools. 321
10.9.1. Description of the process and knowledge model. 321
10.9.2. Modeling with Arena. 322
10.9.3. Modeling and simulation with Witness. 326
10.9.4. Modeling with Quest. 331
10.9.5. Example of modeling of a total logistic chain. 335
10.10. Useful links. 335
10.11. Bibliography. 336
List of Authors. 339
Index. 345 |
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| spelling | Simulation for supply chain management ed. by Caroline Thierry ... London ISTE [u.a.] 2008 XII, 346 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Control systems, robotics and manufacturing series Includes bibliographical references and index "This book provides a detailed insight into the simulation approaches employed in the study of supply chain management and control. It begins by examining the types of simulation models (continuous simulation, discrete-event systems and simulation games) before moving on to the distribution levels of systems and models. It concludes with a thorough discussion of simulation products. Simulation methodologies and techniques are also covered throughout the text and case studies are included to highlight the pivotal role played by simulation in the decision-making processes of those working in this field."--BOOK JACKET. Computersimulaties gtt Ketenbeheer (logistiek) gtt Logistique (organisation) - Simulation par ordinateur ram Logistique (organisation) ram Production - Gestion ram Business logistics Production management Production management Computer simulation Business logistics Computer simulation Supply Chain Management (DE-588)4684051-5 gnd rswk-swf Simulation (DE-588)4055072-2 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Supply Chain Management (DE-588)4684051-5 s Simulation (DE-588)4055072-2 s DE-604 Thierry, Caroline Sonstige oth HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016765213&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Simulation for supply chain management Computersimulaties gtt Ketenbeheer (logistiek) gtt Logistique (organisation) - Simulation par ordinateur ram Logistique (organisation) ram Production - Gestion ram Business logistics Production management Production management Computer simulation Business logistics Computer simulation Supply Chain Management (DE-588)4684051-5 gnd Simulation (DE-588)4055072-2 gnd |
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| title | Simulation for supply chain management |
| title_auth | Simulation for supply chain management |
| title_exact_search | Simulation for supply chain management |
| title_exact_search_txtP | Simulation for supply chain management |
| title_full | Simulation for supply chain management ed. by Caroline Thierry ... |
| title_fullStr | Simulation for supply chain management ed. by Caroline Thierry ... |
| title_full_unstemmed | Simulation for supply chain management ed. by Caroline Thierry ... |
| title_short | Simulation for supply chain management |
| title_sort | simulation for supply chain management |
| topic | Computersimulaties gtt Ketenbeheer (logistiek) gtt Logistique (organisation) - Simulation par ordinateur ram Logistique (organisation) ram Production - Gestion ram Business logistics Production management Production management Computer simulation Business logistics Computer simulation Supply Chain Management (DE-588)4684051-5 gnd Simulation (DE-588)4055072-2 gnd |
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