Bibliographic Information. Stochastic Modeling and Analysis of Manufacturing Systems. David D. Yao. Series Title.
Manufacturing systems have become increasingly complex over recent years. Bibliographic Information.
Manufacturing industries are devoted to producing high-quality products in. .Hardcover: 355 pages.
Manufacturing industries are devoted to producing high-quality products in the most economical and timely manner. This book provides a graduate-level introduction to these techniques covering exact, approximate, and numerical techniques.
modeling manufacturing systems. By means of examples it is illustrated how certain modeling. techniques can be used to derive models that can be used for analysis and/or control. Also, references are provided that can be used as a starting point for getting more details.
Read instantly in your browser. by Alan J. King (Author), Stein W. Wallace (Author). this textbook can indeed be very useful for mathematics students as a methodological guide to the applications of stochastic programming methods. The structure of the textbook is well adapted to teaching purposes.
Principle among these are: Modeling and Analysis of Manufacturing Systems by Askin and Stan-dridge . tion and operations management. Thus, it does not provide the depth and breath of analytical modeling procedures that are presented in this text.
tion and operations management.
This handbook surveys important stochastic problems and models in manufacturing system operations and their stochastic analysis. Using analytical models to design and control manufacturing systems and their operations entail critical stochastic performance analysis as well as integrated optimization models of these systems
Printer: Opaque this. Yao and Zheng: Dynamic Control of Quality in.
Printer: Opaque this. Altiok: Performance Analysis of Manufacturing Systems. Birge and Louveaux: Introduction to Stochastic Programming. Systems: Coordination and Optimization. Yeung and Petrosyan: Cooperative Stochastic Differential Games.
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These papers deal with fundamental questions (how to predict factory performance: how to operate production systems) and explicitly treat the stochastic nature of failures, operation times, demand, and other important events.