Overview
- Editors:
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Andrea Matta
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Politecnico di Milano, Milan, Italy
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Quirico Semeraro
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Politecnico di Milano, Milan, Italy
- Combines decision-making theory, optimization theory, discrete event simulation and queuing networks
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Table of contents (6 chapters)
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- A. Matta, Q. Semeraro, T. Tolio
Pages 1-35
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- M. Bruccoleri, G. Lo Nigro, S. La Noto Diega, P. Renna, G. Perrone
Pages 37-71
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- A. Alfieri, P. Brandimarte
Pages 73-124
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- A. Matta, Q. Semeraro, T. Tolio
Pages 125-189
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- A. Anglani, P. Caricato, A. Grieco, F. Nucci
Pages 191-231
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- F. Caiazzo, R. Pasquino, V. Sergi, B. Spiezio
Pages 233-267
About this book
Since manufacturing has acquired industrial relevance, the problem of adequately sizing manufacturing plants has always been discussed and has represented a di?cult problem for the enterprises, which prepare strategic plans to competitively operate in the market. Manufact- ing capacity is quite expensive and its exploitation and planning must be carefully designed in order to avoid large wastes, or to preserve the survival of enterprises in the market. Indeed a good choice of ma- facturing capacity can result in improved performance in terms of cost, innovativeness, ?exibility, quality and service delivery. Unfortunately the capacity planning problem is not easy to solve because of the lack of clarity in the decisional process, the large number of variables involved, the high correlation among variables and the high level of uncertainty that inevitably a?ects decisions. The aim of this book is to provide a framework and speci?c methods and tools for the selection and con?guration of capacity of Advanced Manufacturing Systems (AMS). In particular this book de?nes an - chitecture where the multidisciplinary aspects of the designofAMSare properly organized and addressed. The tool will support the decisi- maker in the de?nition of the con?guration of the system which is best suited for the particular competitive context where the ?rm operates or wants tooperate. Thisbookisofinterest for academic researchers in the ?eldofind- trial engineering and particularly indicated in the areas of operations and manufacturing strategy.
