Logistic optimization of chemical production processes:
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Weinheim
Wiley-VCH-Verl.
2008
|
| Schlagworte: | |
| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | Literaturangaben |
| Beschreibung: | XIV, 284 S. graph. Darst. |
| ISBN: | 9783527308309 352730830X |
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| 650 | 4 | |a Logistique (Organisation) | |
| 650 | 4 | |a Optimisation mathématique | |
| 650 | 4 | |a Production - Gestion | |
| 650 | 4 | |a Business logistics | |
| 650 | 4 | |a Chemical industry |x Management | |
| 650 | 4 | |a Production management | |
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Datensatz im Suchindex
| _version_ | 1804137769155428352 |
|---|---|
| adam_text | I v
Contents
Preface IX
List of Contributors XIII
Parti Introduction
1 Supply Chain and Supply Chain Management 3
Mario Stobhe
1.1 Introduction 3
1.2 Terms and Definitions 3
1.3 Network Dynamics and Management of the Supply Chain 6
1.4 Design Criteria/Integration Concepts 8
1.5 SCOR: Modeling the Supply Cham 9
1.6 Summary 17
References 18
Part II Simulation
2 Logistics Simulation in the Chemical Industry 21
Markus Schulz and Sven Spieckirmann
2.1 Introduction 21
2.2 Areas of Application for Logistics Simulation in the
Process Industry 21
2.3 The Simulation Process in Manufacturing and Logistics 23
2.4 Case Studies 26
2.5 Benefits and Expenses of Simulation Projects 33
2.6 How a Simulator Works 34
2.7 Developments in the Field of Logistics Simulation 35
References 36
vi moments
3 Logistic Simulation of Pipeless Plants 37
Andreas Liefeldt
3.1 Pipeless Batch Plants 37
3.2 PPSiM-Pipeless Plant Simulation 39
3.3 Industrial Case Study 44
3.4 Conclusions 54
References 55
Part III Industrial Solutions
4 Planning Large Supply Chain Scenarios with Quant-based
Combinatorial Optimization 59
Christoph Plapp, Dirk Surholt, and Dietmar Syring
4.1 Introduction 59
4.2 The Limits of Traditional LP 59
4.3 Quant-based Combinatorial Optimization 61
4.4 Typical Planning Scenarios in the Process Industry 63
4.5 Constraints 64
4.6 Additional Modeling Elements of the Quant-based Combinatorial
Optimization 65
4.7 The Solution Approach 66
4.8 Special Requirements and Advanced Modeling Features for the
Chemical Industry 68
4.9 Summary 89
References 89
5 Scheduling and Optimization of a Copper Production Process 93
Iiro Hatjunkoski, Marco Fahl, and Hans Werner Borchers
5.1 Introduction 93
5.2 Copper Production Process 94
5.3 Scheduling Problem 96
5.4 Solution Approach 99
5.5 Results 106
5.6 Conclusions 107
References 109
6 Stochastic Tools in Supply Chain Management 111
RudolfMetz
6.1 I ntroduction 111
6.2 Random Demand 112
6.3 Random Service (and Shortage) 120
6.4 Optimization of Service 124
6.5 Solution Technique 127
6.6 I mplementation in B ayAP S P P 130
References 133
contents I vn
Part IV Optimization Methods
7 Engineered Mixed-Integer Programming in Chemical
Batch Scheduling 137
Guido Sand
7.1 Introduction 137
7.2 The Case Study 138
7.3 An Engineered Approach to Optimal Scheduling 142
7.4 Nonlinear Short-Term Scheduling Model 144
7.5 Linearized Short-Term Model 153
7.6 Comparative Numerical Studies 154
7.7 Conclusions 159
References 160
8 MILP Optimization Models for Short-term Scheduling of
Batch Processes 163
Carlos A. Mendez, Ignacio E. Grossmann, lira Harjunkoski,
and Marco Fahl
8.1 Introduction 163
8.2 Classification of Batch Scheduling Problems 164
8.3 Classification of Optimization Models for Batch Scheduling 166
8.4 Review of Scheduling Models 172
8.5 Computational Comparison Discrete vs Continuous
Approaches 177
8.6 Concluding Remarks and Future Directions 181
8.7 Acknowledgements 182
References 182
9 Uncertainty Conscious Scheduling by Two-Stage Stochastic
Optimization 185
Jochen Till, Guido Sand, and Sebastian Engdl
9.1 Introduction 185
9.2 Scheduling under Uncertainty using a Moving Horizon Approach
with Two-Stage Stochastic Optimization 187
9.3 Two-Stage Stochastic Integer Programming 195
9.4 A Stage Decomposition Based Evolutionary Algorithm 201
9.5 Numerical Studies 205
9.6 Conclusions 212
References 213
10 Scheduling Based on Reachability Analysis of Timed Automata 215
Sebastian Panek, Olaf Stursberg, and Sebastian Engdl
10.1 Introduction 215
10.2 Scheduling with Timed Automata 219
10.3 Reachability Analysis 224
vim ^omems
10.4 Benchmark Example 229
10.5 Summary 233
References 234
PartV Interaction with ERP Systems
11 Integrated Short and Midterm Scheduling of Chemical Production
Processes - A Case Study 239
Mathias Gb bdt, Thomas Kaspe-r, and Christopher Surie
11.1 Introduction 239
11.2 Advanced Planning in Chemical Industries 239
11.3 Case Study 244
11.4 Modeling the Case Study Scenario in rnySAP SCM 246
11.5 Solving the Case Study Scenario in mySAP SCM 254
11.6 Conclusion 260
References 260
12 Integration of Scheduling with ERP Systems 263
Winjried Jaenickc and Robert Sce-ger
12.1 Introduction 263
12.2 Production Scenarios 266
12.3 The Planning Problem and a Solution Approach 268
12A Data Model 270
12.5 Planning Software 272
12.6 Remarks on Planning Philosophy 275
12.7 Remarks on Technical Issues 276
References 277
Index 279
|
| adam_txt |
I v
Contents
Preface IX
List of Contributors XIII
Parti Introduction
1 Supply Chain and Supply Chain Management 3
Mario Stobhe
1.1 Introduction 3
1.2 Terms and Definitions 3
1.3 Network Dynamics and Management of the Supply Chain 6
1.4 Design Criteria/Integration Concepts 8
1.5 SCOR: Modeling the Supply Cham 9
1.6 Summary 17
References 18
Part II Simulation
2 Logistics Simulation in the Chemical Industry 21
Markus Schulz and Sven Spieckirmann
2.1 Introduction 21
2.2 Areas of Application for Logistics Simulation in the
Process Industry 21
2.3 The Simulation Process in Manufacturing and Logistics 23
2.4 Case Studies 26
2.5 Benefits and Expenses of Simulation Projects 33
2.6 How a Simulator Works 34
2.7 Developments in the Field of Logistics Simulation 35
References 36
vi moments
3 Logistic Simulation of Pipeless Plants 37
Andreas Liefeldt
3.1 Pipeless Batch Plants 37
3.2 PPSiM-Pipeless Plant Simulation 39
3.3 Industrial Case Study 44
3.4 Conclusions 54
References 55
Part III Industrial Solutions
4 Planning Large Supply Chain Scenarios with "Quant-based
Combinatorial Optimization" 59
Christoph Plapp, Dirk Surholt, and Dietmar Syring
4.1 Introduction 59
4.2 The Limits of Traditional LP 59
4.3 Quant-based Combinatorial Optimization 61
4.4 Typical Planning Scenarios in the Process Industry 63
4.5 Constraints 64
4.6 Additional Modeling Elements of the Quant-based Combinatorial
Optimization 65
4.7 The Solution Approach 66
4.8 Special Requirements and Advanced Modeling Features for the
Chemical Industry 68
4.9 Summary 89
References 89
5 Scheduling and Optimization of a Copper Production Process 93
Iiro Hatjunkoski, Marco Fahl, and Hans Werner Borchers
5.1 Introduction 93
5.2 Copper Production Process 94
5.3 Scheduling Problem 96
5.4 Solution Approach 99
5.5 Results 106
5.6 Conclusions 107
References 109
6 Stochastic Tools in Supply Chain Management 111
RudolfMetz
6.1 I ntroduction 111
6.2 Random Demand 112
6.3 Random Service (and Shortage) 120
6.4 Optimization of Service 124
6.5 Solution Technique 127
6.6 I mplementation in B ayAP S P P 130
References 133
contents I vn
Part IV Optimization Methods
7 Engineered Mixed-Integer Programming in Chemical
Batch Scheduling 137
Guido Sand
7.1 Introduction 137
7.2 The Case Study 138
7.3 An Engineered Approach to Optimal Scheduling 142
7.4 Nonlinear Short-Term Scheduling Model 144
7.5 Linearized Short-Term Model 153
7.6 Comparative Numerical Studies 154
7.7 Conclusions 159
References 160
8 MILP Optimization Models for Short-term Scheduling of
Batch Processes 163
Carlos A. Mendez, Ignacio E. Grossmann, lira Harjunkoski,
and Marco Fahl
8.1 Introduction 163
8.2 Classification of Batch Scheduling Problems 164
8.3 Classification of Optimization Models for Batch Scheduling 166
8.4 Review of Scheduling Models 172
8.5 Computational Comparison Discrete vs Continuous
Approaches 177
8.6 Concluding Remarks and Future Directions 181
8.7 Acknowledgements 182
References 182
9 Uncertainty Conscious Scheduling by Two-Stage Stochastic
Optimization 185
Jochen Till, Guido Sand, and Sebastian Engdl
9.1 Introduction 185
9.2 Scheduling under Uncertainty using a Moving Horizon Approach
with Two-Stage Stochastic Optimization 187
9.3 Two-Stage Stochastic Integer Programming 195
9.4 A Stage Decomposition Based Evolutionary Algorithm 201
9.5 Numerical Studies 205
9.6 Conclusions 212
References 213
10 Scheduling Based on Reachability Analysis of Timed Automata 215
Sebastian Panek, Olaf Stursberg, and Sebastian Engdl
10.1 Introduction 215
10.2 Scheduling with Timed Automata 219
10.3 Reachability Analysis 224
vim ^omems
10.4 Benchmark Example 229
10.5 Summary 233
References 234
PartV Interaction with ERP Systems
11 Integrated Short and Midterm Scheduling of Chemical Production
Processes - A Case Study 239
Mathias Gb'bdt, Thomas Kaspe-r, and Christopher Surie
11.1 Introduction 239
11.2 Advanced Planning in Chemical Industries 239
11.3 Case Study 244
11.4 Modeling the Case Study Scenario in rnySAP SCM 246
11.5 Solving the Case Study Scenario in mySAP SCM 254
11.6 Conclusion 260
References 260
12 Integration of Scheduling with ERP Systems 263
Winjried Jaenickc and Robert Sce-ger
12.1 Introduction 263
12.2 Production Scenarios 266
12.3 The Planning Problem and a Solution Approach 268
12A Data Model 270
12.5 Planning Software 272
12.6 Remarks on Planning Philosophy 275
12.7 Remarks on Technical Issues 276
References 277
Index 279 |
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| id | DE-604.BV023391597 |
| illustrated | Illustrated |
| index_date | 2024-07-02T21:20:11Z |
| indexdate | 2024-07-09T21:17:33Z |
| institution | BVB |
| isbn | 9783527308309 352730830X |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016574528 |
| oclc_num | 181069639 |
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| owner_facet | DE-703 |
| physical | XIV, 284 S. graph. Darst. |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Wiley-VCH-Verl. |
| record_format | marc |
| spelling | Logistic optimization of chemical production processes ed. by Sebastian Engell Weinheim Wiley-VCH-Verl. 2008 XIV, 284 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Literaturangaben Industries chimiques - Gestion Industries chimiques - Gestion - Modèles mathématiques Logistique (Organisation) Optimisation mathématique Production - Gestion Business logistics Chemical industry Management Production management Supply Chain Management (DE-588)4684051-5 gnd rswk-swf Enterprise-Resource-Planning (DE-588)4678022-1 gnd rswk-swf Chemische Verfahrenstechnik (DE-588)4069941-9 gnd rswk-swf Prozessoptimierung (DE-588)4176074-8 gnd rswk-swf Chemische Industrie (DE-588)4009848-5 gnd rswk-swf Logistik (DE-588)4036210-3 gnd rswk-swf Chemische Industrie (DE-588)4009848-5 s Supply Chain Management (DE-588)4684051-5 s Logistik (DE-588)4036210-3 s Enterprise-Resource-Planning (DE-588)4678022-1 s Prozessoptimierung (DE-588)4176074-8 s DE-604 Chemische Verfahrenstechnik (DE-588)4069941-9 s Engell, Sebastian Sonstige oth text/html http://deposit.dnb.de/cgi-bin/dokserv?id=2620813&prov=M&dok_var=1&dok_ext=htm Inhaltstext HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016574528&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Logistic optimization of chemical production processes Industries chimiques - Gestion Industries chimiques - Gestion - Modèles mathématiques Logistique (Organisation) Optimisation mathématique Production - Gestion Business logistics Chemical industry Management Production management Supply Chain Management (DE-588)4684051-5 gnd Enterprise-Resource-Planning (DE-588)4678022-1 gnd Chemische Verfahrenstechnik (DE-588)4069941-9 gnd Prozessoptimierung (DE-588)4176074-8 gnd Chemische Industrie (DE-588)4009848-5 gnd Logistik (DE-588)4036210-3 gnd |
| subject_GND | (DE-588)4684051-5 (DE-588)4678022-1 (DE-588)4069941-9 (DE-588)4176074-8 (DE-588)4009848-5 (DE-588)4036210-3 |
| title | Logistic optimization of chemical production processes |
| title_auth | Logistic optimization of chemical production processes |
| title_exact_search | Logistic optimization of chemical production processes |
| title_exact_search_txtP | Logistic optimization of chemical production processes |
| title_full | Logistic optimization of chemical production processes ed. by Sebastian Engell |
| title_fullStr | Logistic optimization of chemical production processes ed. by Sebastian Engell |
| title_full_unstemmed | Logistic optimization of chemical production processes ed. by Sebastian Engell |
| title_short | Logistic optimization of chemical production processes |
| title_sort | logistic optimization of chemical production processes |
| topic | Industries chimiques - Gestion Industries chimiques - Gestion - Modèles mathématiques Logistique (Organisation) Optimisation mathématique Production - Gestion Business logistics Chemical industry Management Production management Supply Chain Management (DE-588)4684051-5 gnd Enterprise-Resource-Planning (DE-588)4678022-1 gnd Chemische Verfahrenstechnik (DE-588)4069941-9 gnd Prozessoptimierung (DE-588)4176074-8 gnd Chemische Industrie (DE-588)4009848-5 gnd Logistik (DE-588)4036210-3 gnd |
| topic_facet | Industries chimiques - Gestion Industries chimiques - Gestion - Modèles mathématiques Logistique (Organisation) Optimisation mathématique Production - Gestion Business logistics Chemical industry Management Production management Supply Chain Management Enterprise-Resource-Planning Chemische Verfahrenstechnik Prozessoptimierung Chemische Industrie Logistik |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=2620813&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016574528&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT engellsebastian logisticoptimizationofchemicalproductionprocesses |