Performance Analysis of Manufacturing Systems

  • Tayfur Altiok

Part of the Springer Series in Operations Research book series (ORFE)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Tayfur Altiok
    Pages 15-65
  3. Tayfur Altiok
    Pages 66-117
  4. Tayfur Altiok
    Pages 118-184
  5. Tayfur Altiok
    Pages 185-242
  6. Tayfur Altiok
    Pages 243-272
  7. Tayfur Altiok
    Pages 273-351
  8. Back Matter
    Pages 353-355

About this book


Manufacturing industries are devoted to producing high-quality products in the most economical and timely manner. Quality, economics, and time not only indicate the customer-satisfaction level, but also measure the manufacturing per­ formance of a company. Today's manufacturing environments are becoming more and more complex, flexible, and information-intensive. Companies invest into the information technologies such as computers, communication networks, sensors, actuators, and other equipment that give them an abundance of information about their materials and resources. In the face of global competition, a manufacturing company's survival is becoming more dependent on how best this influx of in­ formation is utilized. Consequently, there evolves a great need for sophisticated tools of performance analysis that use this information to help decision makers in choosing the right course of action. These tools will have the capability of data analysis, modeling, computer simulation, and optimization for use in designing products and processes. International competition also has had its impact on manufacturing education and the government's support of it in the US. We see more courses offered in this area in industrial engineering and manufacturing systems engineering departments, operations research programs, and business schools. In fact, we see an increasing number of manufacturing systems engineering departments and manufacturing research centers in universities not only in the US but also in Europe, Japan, and many developing countries.


Analysis Manufacturing Manufacturing System Stochastic model Stochastic modelling modeling operations research

Authors and affiliations

  • Tayfur Altiok
    • 1
  1. 1.Department of Industrial EngineeringRutgers UniversityPiscatawayUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag New York Inc. 1997
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-7341-7
  • Online ISBN 978-1-4612-1924-8
  • Series Print ISSN 1431-8598
  • Buy this book on publisher's site
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