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Soft Computing and Fractal Theory for Intelligent Manufacturing

  • Book
  • © 2003

Overview

Authors:
  1. Oscar Castillo

    1. Department of Computer Science, Tijuana Institute of Technology, Chula Vista, USA
      Tijuana, B. C., Mexico

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  2. Patricia Melin

    1. Department of Computer Science, Tijuana Institute of Technology, Chula Vista, USA
      Tijuana, B. C., Mexico

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    You can also search for this author in PubMed   Google Scholar

  • Unique approach combining soft computing techniques with fractal theory
  • Various applications in manufacturing, numerous examples
  • Includes supplementary material: sn.pub/extras

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

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xiv
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  2. Introduction

    • Oscar Castillo, Patricia Melin
    Pages 1-4

  3. Type-1 Fuzzy Logic

    • Oscar Castillo, Patricia Melin
    Pages 5-31

  4. Type-2 Fuzzy Logic

    • Oscar Castillo, Patricia Melin
    Pages 33-46

  5. Supervised Learning Neural Networks

    • Oscar Castillo, Patricia Melin
    Pages 47-73

  6. Unsupervised Learning Neural Networks

    • Oscar Castillo, Patricia Melin
    Pages 75-92

  7. Genetic Algorithms and Simulated Annealing

    • Oscar Castillo, Patricia Melin
    Pages 93-125

  8. Dynamical Systems Theory

    • Oscar Castillo, Patricia Melin
    Pages 127-149

  9. Plant Monitoring and Diagnostics

    • Oscar Castillo, Patricia Melin
    Pages 151-165

  10. Adaptive Control of Non-Linear Plants

    • Oscar Castillo, Patricia Melin
    Pages 167-184

  11. Automated Quality Control in Sound Speaker Manufacturing

    • Oscar Castillo, Patricia Melin
    Pages 185-206

  12. Intelligent Manufacturing of Television Sets

    • Oscar Castillo, Patricia Melin
    Pages 207-225

  13. Intelligent Manufacturing of Batteries

    • Oscar Castillo, Patricia Melin
    Pages 227-266

  14. Back Matter

    Pages 267-283
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Keywords

About this book

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.

Authors and Affiliations

  • Department of Computer Science, Tijuana Institute of Technology, Chula Vista, USA

    Oscar Castillo, Patricia Melin

  • Tijuana, B. C., Mexico

    Oscar Castillo, Patricia Melin

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