Designing simulation experiments for evaluating manufacturing systems

Simulation experiments can benefit from proper planning and design, which can often increase the precision of estimates and strengthen confidence in conclusions drawn from the simulations. While simulation experiments are broadly similar to any statistical experiment, there are a number of differences. In particular, it is often possible to exploit the control of random numbers used to drive the simulation model. To illustrate the methodology described, four examples drawn from manufacturing are used.