Artificial Intelligence in Industrial Decision Making, Control and Automation

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This book is concerned with Artificial Intelligence (AI) concepts and techniques as applied to industrial decision making, control and automation problems. The field of AI has been expanded enormously during the last years due to that solid theoretical and application results have accumulated. During the first stage of AI development most workers in the field were content with illustrations showing ideas at work on simple problems. Later, as the field matured, emphasis was turned to demonstrations that showed the capability of AI techniques to handle problems of practical value. Now, we arrived at the stage where researchers and practitioners are actually building AI systems that face real-world and industrial problems. This volume provides a set of twenty four well-selected contributions that deal with the application of AI to such real-life and industrial problems. These contributions are grouped and presented in five parts as follows: Part 1: General Issues Part 2: Intelligent Systems Part 3: Neural Networks in Modelling, Control and Scheduling Part 4: System Diagnostics Part 5: Industrial Robotic, Manufacturing and Organizational Systems Part 1 involves four chapters providing background material and dealing with general issues such as the conceptual integration of qualitative and quantitative models, the treatment of timing problems at system integration, and the investigation of correct reasoning in interactive man-robot systems.


The field of artificial intelligence (AI) has expanded enormously during the last years, and solid theoretical and application results are now available. Researchers and practitioners are building AI-based systems that face real-world and industrial problems. emArtificial Intelligence in Industrial Decision Making,/em emControl and Automation/em provides a balanced state-of-the-art presentation of the involvement of AI in the design and operation of important industrial systems with built-in intelligence. Topics included are: integration of qualitative and quantitative models, timing problems, intelligent simulation and control, multiresolutional architectures for autonomous systems, DAI systems, artificial neural networks in modelling and control, system diagnostics, industrial robotic systems and cells, man-robot systems, flexible manufacturing systems, knowledge-based scheduling systems. br/ Readers can save considerable time in searching the scattered literature in the field, and can find here a rich set of how-to-do issues and results which will improve their skills in analyzing and designing AI-based systems. br/

Preface. Part 1: General Issues. 1. Artificial Intelligence in Industrial Decision Making, Control and Automation: an Introduction; S.G. Tzafestas, H. Verbruggen. 2. Conceptual integration of Qualitative and Quantitative Process Models; E.A. Woods. 3. Timing Problems and their Handling at System Integration; L. Motus. 4. Analysis for Correct Reasoning in Interactive Man Robot Systems: Disjunctive Syllogism with Modus ponens and Modus tollens; E.C. Koenig. Part 2: Intelligent Systems. 5. Applied Intelligent Control Systems: R. Shoureshi, M. Wheeler, L. Brackney. 6. Intelligent Simulation in Designing Complex Dynamic Control Systems; F. Zhao. 7. Multiresolutional Architectures for Autonomous Systems with Incomplete and Indequate Knowledge Representation; A. Meysel. 8. Distributed Intelligent Systems in Cellular Robotics; T. Fuikuda, T. Ueyama, K. Sekiyama. 9. Distributed Artificial Intelligence in Manufacturing Control; S. Albayrak, H. Krallmann. Part 3: Neural Networks in Modelling, Control and Scheduling. 10. Artificial Neural Networks for Modelling; A.J. Krijgsman, H.B. Verbruggen, P.M. Bruijn. 11. Neural Networks in Robot Control; S.G. Tzafestas. 12. Control Strategy of Robotic Manipulator Based on Flexible Neural Network Structure; M. Teshnehlab, K. Watanabe. 13. Neuro-Fuzzy Approaches to Anticipatory Control; L.H. Tsoukalas, A. Ikonomopoulos, R.E. Uhrig. 14. New Approaches to Large-Scale Scheduling Problems: Constraint Directed Programming and Neural Networks; Y. Kobayashi, N. Nonaka. Part 4: Systems Diagnostics. 15. Knowledge-Based Fault Diagnosis of Technological Systems; H.B. Verbruggen, S.G. Tzafestas, E. Zanni. 16. Model-Based Diagnosis: State Transition Events and Constraint Equations; K.-E. Arzen, A. Wallen, T.F. Petti. 17. Diagnosis with Explicit Models of Goals and Functions; J.E. Larsson. Part 5: Industrial Robotic, Manufacturing and Organizational Systems. 18. Multi-Sensor Integration for Mobile Robot Navigation; A. Traca de Almeida, H. Araujo, J. Dias, U. Nunes. 19. Incremental Design of a Flexible Robotic Assembly Cell Using Reactive Robots; E.s. Tzafestas, S.G. Tzafestas. 20. On the Comparison of AI and DAI Based Planning Techniques for Automated Manufacturing Systems; A.I. Kokkinaki, K.P. Valavanis. 21. Knowledge-Based Supervision of Flexible Manufacturing Systems; A.K.A. Toguyeni, E. Craye, J.-C. Gentina. 22. A Survey of Knowledge-Based Industrial Scheduling; K.S. Hindi, M.g. Singh. 23. Reactive Batch Scheduling; V.J. Terpstra, H.B. Verbruggen. 24. Applying Groupware Technologies to Support Management in Organizations; A. Michailidis, P.-I. Gouma, R. Rada. Index.

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Artificial Intelligence in Industrial Decision Making, Control and Automation
Kartonierter Einband
Springer Netherlands
Anzahl Seiten
H240mm x B160mm x T42mm
Softcover reprint of the original 1st ed. 1995
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