Characterizing and Modelling uncertainties in Production systems

Numerous decisions must be taken within the framework of conception, optimization and management of production system or supply chain. With this aim, managers need to model their systems. Unfortunately, data can be imprecise at the design stage or can evolve during the exploitation of the system. However, data can have a deep impact on the system performance. Thus, decision-makers have to take into account these uncertainties and use the appropriate tools and methodology to model them. In this paper we propose a conceptual framework for imperfect data characterizing and modelling. The goal of this framework is to provide a decision tool to help users to choose the most suitable modelling approach for their manufacturing system problems.