Selecting capacity plan: Dealing with non-stochastic uncertainty in the capacity planning process

Nowadays, the frequency of decisions related with the configuration and capacity evaluation of manufacturing production system is increasing in more and more industrial sectors. In such a context, decision-makers have to take their actions in shorter times than they ever did in the past. This problem has increased in complexity because of the necessity to take into account all the sources of variability and each related level of uncertainty in the available data definition. For such a reason the capacity plan selection process is still an open question. In this chapter, a Decision Support System has been developed to help decision-makers to take productive capacity planning decisions according to uncertain characterization of the market evolution. The proposed methodology can be used to take strategic decisions over a long term programming horizon, allowing an effective comparison of user-defined strategies according to user-defined efficiency parameters. In the proposed approach, the strategy expansion evaluation concerns the designing of the state evolution, the representation of the system dynamic and the research of the suitable capacity plan. Finally, our approach has been validated by means of the reference case study. © 2005 Springer