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Intelligent Quality Systems

Although the tenn quality does not have a precise and universally accepted definition, its meaning is generally well understood: quality is what makes the difference between success and failure in a competitive world. Given the importance of quality, there is a need for effective quality systems to...

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Bibliographic Details
Main Authors: Pham, Duc T., Oztemel, Ercan (Author)
Format: eBook
Language:English
Published: London Springer London 1996, 1996
Edition:1st ed. 1996
Series:Advanced Manufacturing
Subjects:
Industrial Engineering
Artificial Intelligence
Industrial And Production Engineering
Production Engineering
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Table of Contents:
  • 1 Introduction
  • 1.1 Quality Assurance Systems
  • 1.2 Knowledge-Based Systems for Quality Control
  • 1.3 Neural Networks for Quality Control
  • 1.4 Integrating Expert Systems and Neural Networks for Quality Control
  • 1.5 Summary
  • References
  • 2 Artificial Intelligence Tools
  • 2.1 Expert Systems
  • 2.2 Neural Networks
  • 2.3 Summary
  • References
  • 3 Statistical Process Control
  • 3.1 Statistical Process Control (SPC) and Control Charting
  • 3.2 XPC: An On-line Expert System for Statistical Process Control
  • 3.3 Intelligent Advisors for Control Chart Selection
  • 3.4 Summary
  • References
  • 4 Control Chart Pattern Recognition
  • 4.1 Control Chart Patterns
  • 4.2 A Knowledge-Based Control Chart Pattern Recognition System
  • 4.3 Using Neural Networks to Recognise Control Chart Patterns
  • 4.4 Composite Systems for Recognising Control Chart Patterns
  • 4.5 Summary
  • References
  • 5 Integrated Quality Control Systems
  • 5.1 The Integration Process
  • 5.2 An Example of Integrating an Expert System with Neural Networks for Quality Control
  • 5.3 Summary
  • References
  • 6 Experimental Quality Design
  • 6.1 Taguchi Experimental Design
  • 6.2 Neural Networks for the Design of Experiments
  • 6.3 Summary
  • References
  • 7 Inspection
  • 7.1 Role of Inspection in Quality Control
  • 7.2 Automated Visual Inspection
  • 7.3 Knowledge-Based Systems for Automated Visual Inspection
  • 7.4 Neural Networks for Automated Visual Inspection
  • 7.5 Discussion
  • 7.6 Summary
  • References
  • 8 Condition Monitoring and Fault Diagnosis
  • 8.1 Condition Monitoring
  • 8.2 Diagnosis
  • 8.3 Discussion
  • 8.4 Summary
  • References
  • Author Index

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