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Titlebook: Design of Advanced Manufacturing Systems; Models for Capacity Andrea Matta,Quirico Semeraro Book 2005 Springer Science+Business Media B.V.

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书目名称Design of Advanced Manufacturing Systems
副标题Models for Capacity
编辑Andrea Matta,Quirico Semeraro
视频video
概述Combines decision-making theory, optimization theory, discrete event simulation and queuing networks
图书封面Titlebook: Design of Advanced Manufacturing Systems; Models for Capacity  Andrea Matta,Quirico Semeraro Book 2005 Springer Science+Business Media B.V.
描述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
出版日期Book 2005
关键词Fuzzy; Operations Research; Simulation; algorithm; algorithms; architecture; environment; fuzzy set; linear
版次1
doihttps://doi.org/10.1007/1-4020-2931-4
isbn_softcover978-90-481-6748-7
isbn_ebook978-1-4020-2931-8
copyrightSpringer Science+Business Media B.V. 2005
The information of publication is updating

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Selecting Capacity Plan,nd more industrial sectors. In such a context, decision-makers have to take their actions in shorter times than they ever did in the past. This problem has increased in complexity because of the necessity to take into account all the sources of variability and each related level of uncertainty in th
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Configuration of AMSs, is closely related to the performance evaluation of the system since discriminating indicators are necessary to rank different alternatives. Approximate stochastic models are proposed to estimate the performance of Advanced Manufacturing Systems. The accuracy of the proposed models is shown by applying them to several test and real cases.
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