Abstract
IMS investments are characterised by high fixed costs and long life cycles. On the other hand, their redditivity and risk coverage depend on their manufacturing efficiency that is mainly defined during the design phase by fixing the system configuration. Due to the flexibility required to IMS, system configuration depends not only from technological information, such as product routing table and service times, but also from marketing data such as the typology of products to be manufacture and their production volumes. Moreover, the evaluation of the redditivity and the risk of the investment depends on market information such as product prices as well. Such interdependencies make the investment decision environment very complex. Furthermore, the requirements and the data characterising the decision environment are affected by imprecision due to the strategic nature of the decision. Therefore, IMS investment decisions have to be made in a very complex and vague decision environment. Even if, several approaches have been proposed in literature to deal with IMS design problem, very few consider the specific characteristics of the decision environment. In this paper we propose a methodology and a tool that fit very well with the complexity and the vagueness of such design problem. The methodology consists into a simultaneous description of all the requirements, while the tool is the fuzzy possibility theory.
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Perrone, G., La Diega, S.N. (1999). A Simultaneous Approach for IMS Design: a Possibility Based Approach. In: Brandimarte, P., Villa, A. (eds) Modeling Manufacturing Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-03853-6_8
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DOI: https://doi.org/10.1007/978-3-662-03853-6_8
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