Abstract
Manufacturing systems design must provide effective solutions to cope with the demand during the whole system life-cycle. The problem consists of selecting the appropriate set of resources which best fits the requirements of the addressed production problem. When the demand is characterized by a family of products undergoing technological and volume modifications, the system design process becomes quite complicated. Starting from present and forecasted information, machine tool builders have to design systems endowed with the flexibility and reconfigurability levels that enable the system to face the production problem variability during its life. In spite of the relevance of this topic, there is a lack of tools to explicitly design system flexibility and reconfigurability considering the uncertainty affecting the problem. By addressing two main types of uncertainty, i.e. demand variability and resource availability, this chapter presents a solution method based on multi-stage stochastic programming, to support the design of new manufacturing system architectures whose level of flexibility is focused on the specific production requirements. The problem variability is modeled through scenario trees and the solution is a capacity plan with an initial system configuration and possible reconfigurations. Testing experiments have been carried out considering an industrial case to study the benefits that this approach can offer to machine tool builders.
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Terkaj, W., Tolio, T., Valente, A. (2009). Design of Focused Flexibility Manufacturing Systems (FFMSs). In: Tolio, T. (eds) Design of Flexible Production Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85414-2_7
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DOI: https://doi.org/10.1007/978-3-540-85414-2_7
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