Robust manufacturing design using decision theory

Performance evaluation of a design solution for a manufacturing system is based on a model containing data, supposed to represent future exploitation conditions. Unfortunately, data can be imprecise at the design stage or can evolve during the exploitation of the system. However, these data can have a deep impact on the system performance. Therefore, it is necessary to take into account possible evolutions of exploitation conditions at the design stage and to compare solutions regarding their performance on several potential environments, i.e. regarding their robustness. Thus, the decision-makers have to choose a solution among several, regarding its behavior and its performance under several operating conditions. Furthermore, they need tools to support their decisions, which allow justifying mathematically their choice. In this article, we propose an approach based on decision theory able to help manager in the area of design of manufacturing system taking into account possible variation of production environment, by bringing mathematical tools and robustness measures