Simplification in the simulation of manufacturing systems

Given the widespread acceptance of the importance of simplicity in management science models, the scarcity of research into simplification is perhaps surprising. In the simulation of manufacturing systems, simplification is often not attempted and, on the (misguided) assumption that more detailed models are necessarily more accurate and therefore better, common practice is to build and use the most complex model that can be built in the time available. However, for cases where the only results required are averages, such as long term throughput rates, it will often be possible to reduce the model to such a simple version that an analytical solution becomes feasible and the simulation redundant. An eight stage procedure is proposed for doing the reductions and two manufacturing case studies are described.