Stochastic Modeling of Manufacturing Systems Advances in Design, Per
Manufacturing systems rarely perform exactly as expected and predicted. Unexpected events, such as order changes, equipment failures and product defects, affect the performance of the system and complicate decision-making. This volume is devoted to the de
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G. Liberopoulos · C. T. Papadopoulos · B. Tan J. MacGregor Smith · S. B. Gershwin Editors
Stochastic Modeling of Manufacturing Systems Advances in Design, Performance Evaluation, and Control Issues
With 121 Figures and 91 Tables
123
George Liberopoulos Department of Mechanical and Industrial Engineering University of Thessaly 38334 Volos Greece E-mail: [email protected]
J. M. Smith Department of Mechanical and Industrial Engineering University of Massachusetts Amherst, Massachusetts 01003 USA E-mail: [email protected]
Chrissoleon T. Papadopoulos Department of Economic Sciences Aristotle University of Thessaloniki 54124 Thessaloniki Greece E-mail: [email protected]
Stanley B. Gershwin Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge, Massachusetts 02139-4307 USA E-mail: [email protected]
Barıs¸ Tan Graduate School of Business Koç University 80910 Sariyer, Istanbul Turkey E-mail: [email protected]
Parts of the papers of this volume have been published in the journal OR Spectrum.
Library of Congress Control Number: 2005930501
ISBN-10 3-540-26579-1 Springer Berlin Heidelberg New York ISBN-13 978-3-540-26579-5 Springer Berlin Heidelberg New York This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer-Verlag. Violations are liable for prosecution under the German Copyright Law. Springer is a part of Springer Science+Business Media springeronline.com © Springer-Verlag Berlin Heidelberg 2006 Printed in Germany The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover design: Erich Kirchner Production: Helmut Petri Printing: Strauss Offsetdruck SPIN 11506560
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Editorial – Stochastic Modeling of Manufacturing Systems: Advances in Design, Performance Evaluation, and Control Issues
Manufacturing systems rarely perform exactly as expected and predicted. Unexpected events always happen: customers may change their orders, equipment may break down, workers may be absent, raw parts may not arrive on time, processed parts may be defective, etc. Such randomness affects the performance of the system and complicates decision-making. Responding to unexpected disturbances occupies a significant amount of time of manufacturing managers. There are two possible plans of action for addressing randomness: reduce it or respond to it in a way that limits its corrupting effect on system pe
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