A unique view of intelligent production management and technologies for today s competitive manufacturing environment Focuses on the planning and scheduling of production systems for Job Shop Manufacturing and Re–entrant Manufacturing Highlights the advanced research works in the field of industrial engineering and management, such as numerical optimization methods and wireless sensor networks Enables students, researchers and engineers to understand the fundamentals and theories of multi–agent based production planning and control Written by an author with more than 20 years experience in this area, it is the result of her study and formulation of a complete theoretical system in these technologies Fully illustrated throughout, the methods for production planning, scheduling and controlling are presented using experiments, numerical simulations and theoretical analysis INDICE: Preface .About this book .Chapter 1 Agent Technology in Modern Manufacturing 1 .1.1 Introduction 1 .1.2 Agent and Multi–Agent System 1 .1.2.1 Agent 1 .1.2.2 Multi–Agent System 4 .1.3 Agent technologies in manufacturing systems 6 .1.3.1 Contemporary Manufacturing System 6 .1.3.2 Agents in production planning and control systems 7 .1.3.3 The existing requirements 9 .1.4 Book Organization 9 .1.4.1 Purpose of the Book 9 .1.4.2 Scope of the Book 10 .1.4.3 Content of the Book 11 .References 12 .Chapter 2 The Technical Foundation of A Multi–Agent System 17 .2.1 Introduction 17 .2.2 The Structure of An Agent 17 .2.2.1 Thinking Agent 19 .2.2.2 Reactive Agent 22 .2.2.3 Hybrid Agent 23 .2.3 The Structure of A Multi–Agent System 25 .2.3.1 The Environment of A Multi–Agent System 25 .2.3.2 The Structure of A Multi–Agent System 25 .2.4 Modeling Methods of A Multi–Agent System 28 .2.4.1 The Behavior Model of A Multi–Agent System 29 .2.4.2 The Running Model of A Multi–Agent System 30 .2.5 The Communication and Interaction Model of A Multi–Agent System 32 .2.6 The Communication Protocol for A Multi–Agent System 33 .2.6.1 Communication Languages for An Agent 34 .2.6.2 The Communication Ontology for An Agent 36 .2.7 The Interaction Protocol for A Multi–Agent System 37 .2.7.1 Classification of Interaction Protocols 38 .2.7.2 Description of Interaction Protocols 39 .2.7.3 The Collaboration–based Interaction Protocol 41 .2.7.4 The Negotiation–based Interaction Protocol 42 .2.8 Conclusion 44 .References 44 .Chapter 3 Multi–Agent–based Production Planning and Control 47 .3.1 Introduction 47 .3.2 Manufacturing Systems 47 .3.2.1 Concept 47 .3.2.2 Classification 48 .3.3 Production Planning and Control 52 .3.3.1 Production Planning and Control Activities 52 .3.3.2 Production Planning and Control Mode 54 .3.3.3 Production Planning and Control Systems 55 .3.3.4 Hybrid Push–pull Production Planning and Control System 56 .3.4 Multi–Agent–based Push–pull Production Planning and Control System (MAP4CS) 59 .3.4.1 Mapping Methods 59 .3.4.2 Functions of a Hybrid Push–pull Production Planning and Control System 60 .3.4.3 Structures of a MAP4CS 63 .3.4.4 The Running Model of a MAP4CS 66 .3.4.5 Behavior Models of a MAP4CS 67 .3.4.6 The Interactive Model of a MAP4CS 69 .3.5 Conclusion 73 .References 73 .Chapter 4 Multi–Agent–based Production Planning for Distributed Manufacturing Systems 75 .4.1 Introduction 75 .4.2 Production Planning for Distributed Manufacturing Systems 75 .4.2.1 Distributed Manufacturing Systems 75 .4.2.2 Features of Distributed Manufacturing Systems 77 .4.2.3 Production Planning Methods for Distributed Manufacturing Systems 80 .4.3 Multi–Agent–based Production Planning in Distributed Manufacturing Systems 83 .4.3.1 A Production Planning Model for Distributed Manufacturing Systems 83 .4.3.2 Production Planning in MASs 88 .4.3.3 The Running Model of a Multi–agent–based Production Planning System 91 .4.4 Agents in Multi–agent Production Planning Systems 92 .4.4.1 Order Demand Management Agent 92 .4.4.2 Cooperative Planning Agent 94 .4.4.3 Critical Resource Capacity Management Agent 95 .4.5 Contract Net Protocol Based Production Planning Optimization Method 97 .4.5.1 Contract Net Protocol 97 .4.5.2 Contract Net Protocol based Collaborative Production Planning Algorithm 99 .4.5.3 Case Study 102 .4.6 Bid Auction Protocol based Production Planning Optimization Method 104 .4.6.1 Bid Auction Protocol 104 .4.6.2 Bid Auction Protocol based Negotiating Production Planning Algorithm 105 .4.6.3 Case Study 108 .4.7 Conclusions 109 .References 109 .Chapter 5 Multi–Agent–based Production Scheduling for Job Shop Manufacturing Systems 111 .5.1 Introduction 111 .5.2 Production Scheduling in Job Shop Manufacturing Systems 111 .5.2.1 Job Shop Manufacturing Systems 112 .5.2.2 Production Scheduling in Job Shop Manufacturing Systems 114 .5.2.3 The Related Literature Review 115 .5.3 Multi–Agent Double Feedback Based Production Scheduling in Job Shop Manufacturing Systems 121 .5.3.1 Principles of Double Feedback Scheduling Strategy 121 .5.3.2 The Architecture of Multi–Agent Double Feedback based Production Scheduling System 122 .5.3.3 The Running Model for Multi–agent Double Feedback based Production Scheduling 123 .5.4 Agents in Multi–agent Double Feedback Based Scheduling System 125 .5.4.1 Task Management Agent 125 .5.4.2 Collaborative Scheduling Agent 126 .5.4.3 Resource Capacity Management Agent 128 .5.5 Positive Feedback Based Production Scheduling in Job Shop Manufacturing Systems 128 .5.5.1 Problem Description 129 .5.5.2 Multi–agent Positive Feedback Scheduling System based on Contract Net Protocol 133 .5.5.3 Positive Feedback Production Scheduling Algorithm Based on the Hierarchical Genetic Algorithm 134 .5.5.4 Case Study 139 .5.6 Negative Feedback Based Production Rescheduling in Job Shop Manufacturing Systems 141 .5.6.1 Problem Description 141 .5.6.2 Multi–agent Negative Feedback Rescheduling System based on Ant Colony Auction Protocol 143 .5.6.3 Ant Colony Algorithm based Negative Feedback Rescheduling approach 145 .5.6.4 Case Study 150 .5.7 Conclusion 151 .References 152 .Chapter 6 Multi–Agent–based Production Scheduling in Re–entrant Manufacturing Systems 156 .6.1 Introduction 156 .6.2 Production Scheduling in Re–Entrant Manufacturing Systems 156 .6.2.1 Re–Entrant Manufacturing Systems 157 .6.2.2 Production Scheduling in Re–Entrant Manufacturing Systems 160 .6.2.3 The Related Literature Review 163 .6.3 Multi–Agent–Based Hierarchical Adaptive Production Scheduling in Re–entrant Manufacturing Systems 167 .6.3.1 Hierarchical Adaptive Production Scheduling Strategy 167 .6.3.2 The Architecture of Multi–Agent Hierarchical Adaptive Production Scheduling System 168 .6.3.3 The Running Model for Multi–Agent Hierarchical Adaptive Production Scheduling System 170 .6.4 Agents in Multi–Agent Hierarchical Adaptive Production Scheduling System 171 .6.4.1 Task Management Agent 171 .6.4.2 Collaborative Scheduling Agent 173 .6.4.3 Resource Capacity Management Agent 174 .6.5 Hierarchical Production Scheduling in Re–entrant Manufacturing Systems 175 .6.5.1 Problem Description 176 .6.5.2 Contact Net Protocol based Production Scheduling in the System Layer 179 .6.5.3 GPGP–CN Protocol Based Production Scheduling in the Machine Layer 183 .6.5.4 Case Study 193 .6.6 Adaptive Rescheduling in Re–entrant Manufacturing Systems 196 .6.6.1 Problem Description 197 .6.6.2 Rescheduling Strategy 199 .6.6.3 FNN based Rescheduling 200 .6.6.4 Case Study 204 .6.7 Conclusion 206 .References 207 .Chapter 7 Multi–Agent–Based Production Control 210 .7.1 Introduction 210 .7.2 Multi–Agent Production Control System 210 .7.2.1 Requirements of Production Control Process 210 .7.2.2 The Architecture of Multi–Agent Production Control System 211 .7.2.3 The Running Model for Multi–Agent Production Control Systems 214 .7.3 Agents in Multi–Agent Production Control Systems 216 .7.3.1 Collaborative Task Management Agent 216 .7.3.2 Machine Management Agent 218 .7.3.4 Production Monitoring Agent 219 .7.3.5 Warning Management Agent 220 .7.3.6 Performance Analysis Agent 221 .7.3.7 Quality Management Agent 223 .7.3.8 Production Process Tracking and Tracing Agent 224 .7.4 Technologies and Methods for Multi–Agent Production Control Systems 227 .7.4.1 XML Based Production Monitoring 227 .7.4.2 Differential Manchester Encoding Rule Based Warning Management 228 .7.4.3 Material Identification Technology for Production Process Tracking and Tracing 231 .7.5 Conclusion 237 .References 238 .Chapter 8 Multi–Agent–based Material Data Acquisition 239 .8.1 Introduction 239 .8.2 RFID Technology 239 .8.2.1 Development of RFID Technologies 239 .8.2.2 RFID Technology Standard 242 .8.3 Agent–based Material Data Acquisition System 246 .8.3.1 Requirement Analysis of Material Data Acquisition 246 .8.3.2 Multi–agent RFID–based material data acquision structure 247 .8.3.3 The running model of a multi–agent material data acquisition system 249 .8.4 Agents in Multi–Agent RFID–based Material Data Acquisition Systems 251 .8.4.1 RFID middleware Agent 252 .8.4.2 RFID reader Agent 260 .8.4.3 RFID tag Agent 261 .8.5 Multi–Agent RFID–based Material Data Acquisition Systems 262 .8.5.1 Hardware and configuration 262 .8.5.2 Material data process and publish 264 .8.6 Conclusions 266 .References 266 .Chapter 9 Multi–Agent–based Equipment Data Acquisition 268 .9.1 Introduction 268 .9.2 Basics of OPC Technology 268 .9.2.1 Development of OPC technology 268 .9.2.2 OPC Technology Overview 269 .9.3 Agent–based equipment data acquisition system 272 .9.3.1 Requirement analysis of equipment data acquisition 272 .9.3.2 The MAS structure of OPC–based equipment data acquisition 273 .9.3.3 The running model of equipment data acquisition MAS 275 .9.4 Agents in the multi–agent OPC–based equipment data acquisition system 277 .9.4.1 OPC Agent 277 .9.4.2 OPC server Agent 279 .9.4.3 OPC Client Agent 281 .9.5 Implementation of a Multi–Agent OPC–based System 282 .9.5.1 System Hardware and System Network Architecture 283 .9.5.2 Data integration based on OPC technology 285 .9.6 Conclusions 287 .References 287 .Chapter 10 The Prototype of a Multi–Agent–based Production Planning and Control System 289 .10.1 Introduction 289 .10.2 Architecture of a prototype system 289 .10.2.1 The Software Architecture 289 .10.2.2 The Hardware Architecture 291 .10.3 Agent packages and communication in a prototype system 292 .10.3.1 The Agent package method 292 .10.3.2 The Communication Implementation Model of Agents 294 .10.3.3 The message classification of Agents 295 .10.3.4 Realization of the communication mechanism of Agents 298 .10.4 The Manufacturing System Simulation in a Prototype System 298 .10.4.1 The manufacturing system simulation 299 .10.4.2 The information interaction logic architecture between the prototype system and the simulation model 302 .10.5 Software Implementation and Application of a Prototype System 303 .10.5.1 Function design of a prototype system 303 .10.5.2 The running process of a prototype system 306 .10.5.3 Production planning in distributed manufacturing systems 307 .10.5.4 Production scheduling in Job Shop manufacturing systems 308 .10.5.5 Production scheduling in Re–entrant manufacturing systems 309 .10.5.6 Production control in the manufacturing process 312 .10.6 Conclusions 313 .Reference
- ISBN: 978-1-118-89006-6
- Editorial: Wiley–Blackwell
- Encuadernacion: Cartoné
- Páginas: 440
- Fecha Publicación: 07/06/2017
- Nº Volúmenes: 1
- Idioma: Inglés