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Book Categories |
Preface | ||
1 | Introduction | |
1.1 | Computer-integrated manufacturing system | 1 |
1.2 | Artificial intelligence in manufacturing industry | 7 |
1.3 | Integrated distributed intelligent systems | 29 |
2 | Meta-system architecture | |
2.1 | Meta-system | 35 |
2.2 | Meta-system functions | 39 |
2.3 | Configuration of meta-system | 44 |
2.4 | Meta-system implementation | 47 |
3 | Meta-COOP implementation | |
3.1 | Object-oriented programming technique | 61 |
3.2 | Objects, operations and messages | 64 |
3.3 | Classes and instances | 67 |
3.4 | Methods and information sending | 69 |
3.5 | Active value and facets | 70 |
3.6 | Inheritance | 70 |
3.7 | Rules | 71 |
3.8 | Frame-based knowledge representation and inference | 72 |
3.9 | Rule-based knowledge representation and inference | 76 |
3.10 | Method-based representation and inference | 80 |
3.11 | Core inference | 85 |
3.12 | Interpretation of problem-solving processes | 92 |
3.13 | Case study | 95 |
4 | Integrated distributed intelligent design environment | |
4.1 | Conceptual design of mechanical products | 111 |
4.2 | DAER model | 115 |
4.3 | Problem-solving strategy | 119 |
4.4 | System configuration | 123 |
4.5 | Function and structure conceptual design | 129 |
4.6 | Parameter design | 141 |
4.7 | Scheme analysis | 145 |
4.8 | Comprehensive evaluation | 147 |
4.9 | Decision-making | 152 |
4.10 | Redesign | 155 |
4.11 | Applications | 157 |
5 | Integrated distributed intelligent simulation environment | |
5.2 | IDISE configuration | 180 |
5.3 | Model definition and data structure | 183 |
5.4 | Model base | 184 |
5.5 | Model-based inference | 187 |
5.6 | Separation operation of effective model set | 190 |
5.7 | Generating a homogeneous transformation matrix | 191 |
5.8 | Model assembly | 194 |
5.9 | Fast removing of hidden lines and surfaces | 195 |
5.10 | Collision and interference testing | 197 |
5.11 | Geometric modeling | 198 |
5.12 | IDISE functions | 199 |
5.13 | Examples | 201 |
5.14 | IDISE instruction set | 208 |
6 | Gear integrated distributed intelligent manufacturing system | |
6.2 | Integration architecture | 215 |
6.3 | Functions of the meta-system in GIDIMS | 219 |
6.4 | Modularity of meta-knowledge in GIDIMS | 222 |
6.5 | Standardization of communication in GIDIMS | 223 |
6.6 | Optimal selection of methods | 228 |
7 | Intelligent system for process startup automation | |
7.2 | Process startup operation | 234 |
7.3 | Chemical/mechanical states | 237 |
7.4 | Knowledge acquisition and representation | 239 |
7.5 | Hypertext technique | 243 |
7.6 | Implementation | 244 |
7.7 | Case study | 249 |
8 | Intelligent operation support system for chemical pulp process | |
8.2 | Chemical pulping process operation | 256 |
8.3 | Problem definition | 260 |
8.4 | Problem-solving strategy | 263 |
8.5 | Knowledge acquisition | 264 |
8.6 | Qualitative knowledge representation | 265 |
8.7 | Quantitative computation | 271 |
8.8 | System construction | 279 |
8.9 | Knowledge base organization | 286 |
8.10 | Other advanced system features | 289 |
8.11 | Field testing | 295 |
8.12 | Illustrations | 296 |
References | 305 | |
Further reading | 316 | |
Index | 320 |
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Add Integrated Distributed Intelligent Systems in Manufacturing, Intelligent Manufacturing is a new disciplinary field which applies computer science, artificial intelligence, mechanical engineering and systems science to industrial manufacturing processes. This book presents a new integration architecture for implemen, Integrated Distributed Intelligent Systems in Manufacturing to your collection on WonderClub |