A workload data aggregation process for flexible manufacturing system modeling using queueing network models

In this article, we focus on the use of queueing network (QN) models for quantitatively evaluating the steady-state performance of flexible manufacturing systems (FMSs) at the strategic and tactical decision levels. The first problem encountered with such an approach concerns the description of an FMS, that is, obtaining reliable data from industrial experts. Secondly, when exploited directly, such data (especially those related to FMS workload) often result in a QN model that cannot be analytically or numerically analyzed because of a prohibitive number of customer chains and classes. In this context, we propose a formalization of the workload of an FMS, which is further exploited for defining a systematic workload data aggregation process. This process makes it possible to derive transparently the exact characteristics of a QN model which is much more tractable. The automated data aggregation approach is discussed and its robustness is studied in several examples, one of which is an industrial case.