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Soft Computing and Fractal Theory for Intelligent Manufacturing

  • Oscar Castillo
  • Patricia Melin

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 117)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Oscar Castillo, Patricia Melin
    Pages 1-4
  3. Oscar Castillo, Patricia Melin
    Pages 5-31
  4. Oscar Castillo, Patricia Melin
    Pages 33-46
  5. Oscar Castillo, Patricia Melin
    Pages 47-73
  6. Oscar Castillo, Patricia Melin
    Pages 75-92
  7. Oscar Castillo, Patricia Melin
    Pages 93-125
  8. Oscar Castillo, Patricia Melin
    Pages 127-149
  9. Oscar Castillo, Patricia Melin
    Pages 151-165
  10. Oscar Castillo, Patricia Melin
    Pages 167-184
  11. Oscar Castillo, Patricia Melin
    Pages 185-206
  12. Oscar Castillo, Patricia Melin
    Pages 207-225
  13. Oscar Castillo, Patricia Melin
    Pages 227-266
  14. Back Matter
    Pages 267-283

About this book

Introduction

We describe in this book, new methods for intelligent manufacturing using soft computing techniques and fractal theory. Soft Computing (SC) consists of several computing paradigms, including fuzzy logic, neural networks, and genetic algorithms, which can be used to produce powerful hybrid intelligent systems. Fractal theory provides us with the mathematical tools to understand the geometrical complexity of natural objects and can be used for identification and modeling purposes. Combining SC techniques with fractal theory, we can take advantage of the "intelligence" provided by the computer methods and also take advantage of the descriptive power of the fractal mathematical tools. Industrial manufacturing systems can be considered as non-linear dynamical systems, and as a consequence can have highly complex dynamic behaviors. For this reason, the need for computational intelligence in these manufacturing systems has now been well recognized. We consider in this book the concept of "intelligent manufacturing" as the application of soft computing techniques and fractal theory for achieving the goals of manufacturing, which are production planning and control, monitoring and diagnosis of faults, and automated quality control. As a prelude, we provide a brief overview of the existing methodologies in Soft Computing. We then describe our own approach in dealing with the problems in achieving intelligent manufacturing. Our particular point of view is that to really achieve intelligent manufacturing in real-world applications we need to use SC techniques and fractal theory.

Keywords

Signal Simulation algorithm dynamische Systeme fractal theory fuzzy control fuzzy logic fuzzy system genetic algorithms intelligent manufacturing learning modeling neural networks optimization soft computing

Authors and affiliations

  • Oscar Castillo
    • 1
    • 2
  • Patricia Melin
    • 1
    • 2
  1. 1.Department of Computer ScienceTijuana Institute of TechnologyChula VistaUSA
  2. 2.Tijuana, B. C.Mexico

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-7908-1766-9
  • Copyright Information Physica-Verlag Heidelberg 2003
  • Publisher Name Physica, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-662-00296-4
  • Online ISBN 978-3-7908-1766-9
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site