Given the widespread acceptance of the importance of simplicity in manageme
nt science models, the scarcity of research into simplification is perhaps
surprising. In the simulation of manufacturing systems, simplification is o
ften not attempted and, on the (misguided) assumption that more detailed mo
dels 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 avai
lable. However, for cases where the only results required are averages, suc
h as long term throughput rates, it will often be possible to reduce the mo
del to such a simple version that an analytical solution becomes feasible a
nd the simulation redundant. An eight stage procedure is proposed for doing
the reductions and two manufacturing case studies are described.