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Design and Implementation of Intelligent Manufacturing Systems: From Expert Systems, Neural Networks, to Fuzzy Logic

Design and Implementation of Intelligent Manufacturing Systems: From Expert Systems, Neural Networks, to Fuzzy Logic

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Contents

Prentice Hall Series on Environmental and Intelligent Manufacturing Systems

Series Editor’s Foreword

Ch. 1. Workcell Programming Environment for Intelligent Manufacturing Systems

Ch. 2. An Intelligent System for Automating the Inspection of Manufactured Parts

Ch. 3. An Intelligent Hybrid System for Synthesis and Control of Metal Forming Processes

Ch. 4. Intelligent Diagnostics for Integrated Manufacturing Systems

Ch. 5. Fuzzy Logic Controller for Part Routing

The Linguistic Variables: The Basis for the FLC

Fuzzy Control Rules

Selecting the Control Action

Experimental Results

Ch. 6. Fuzzy-Logic Control as an Industrial Control Language for Embedded Controllers

Ch. 7. Using Neural Networks for the Automatic Monitoring and Recognition of Signals in Manufacturing Processes

Ch. 8. Artificial Neural Network Approach in Modeling of EDM and Wire-EDM Processes

Ch. 9. A Knowledge-Based Expert System for Selection of Industrial Robots

Ch. 10. A Case-Based Knowledge System Employed to Trouble Shoot Failures in a Manufacturing Environment

Ch. 11. Partially Overlapped Systems: The Scheduling Problem

Ch. 12. Object Oriented Approach to Feature-Based Process Planning

Ch. 13. Intelligent Feature Extraction for Concurrent Design and Manufacturing

Ch. 14. CAD in Automatic Machine Programming

Ch. 15. Fault Diagnosis of Large Manufacturing Processes

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