List of Figures nList of Tables nPreface nContributing Authors 1: A framework for long term capacity decisions in AMSs; A. Matta, Q. Semeraro, T. Tolio n1 Introduction n2 Manufacturing capacityn3 Manufacturing strategyn4 Advanced Manufacturing Systemsn5 A framework for capacity problems 2: A DSS for strategic planning; M. Bruccoleri, G. Lo Nigro, S. Noto La Diega, P. Retina, C. Perronen1 The strategic planning process n2 Models for Production Strategy Planning n3 Models for Long-term Capacity Planning n4 DSS descriptionn5 Tests and resultsn6 Conclusions 3: Stochastic programming models for manufacturing applications; A. Alfieri, P. Brandimarten1 Introduction n2 The newsvendor problem n3 Stochastic linear programmingn4 General structure of two-stage stochastic linear programs n5 Solution methodsn6 Multi-stage stochastic programming models n7 Strong mixed-integer model formulations n8 Scenario generation n9 Models for capacity planningn10 An alternative approach to cope with uncertainty: robust optimization n11 Conclusions 4: Configuration of AMSs; A. Matta. Q. Semeraro. T. Tolio n1 Introduction n2 Problem description n3 Description of Automated Manufacturing Systems n4 Design of Automated Manufacturing Systems n5 Performance evaluation of Dedicated Manufacturing Flow Lines n6 Performance evaluation of Flexible Manufacturing Systems n7 Conclusions 5: Selecting capacity plan; A. Anglani, P. Caricato, A. Grieco, F. Nucci n1 Introduction n2 Problem statementn3 The proposed methodology n4 Case study n5 Conclusions 6: Fuzzy performance evaluator of AMSs; F. Caiazzo, R. Pasquino, V. Sergi, B. Spiezio n1 Introduction n2 Fuzzy sets arid fuzzy numbers n3 Describing uncertainty n4 Linguistic modifiers n5 Constructing fuzzy sets n6 Queuing systems n7 Open queuing network modelsn8 Closed queuing network models n9 The method proposed: single-class case n10 The method proposed: multi-class case n11 The algorithm for the method proposed: single-class case n12 A sample application n13 Conclusions
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.
Combines decision-making theory, optimization theory, discrete event simulation and queuing networks