Insights into process reliability through simulation

System dynamics modeling of complex processes as a set of coupled nonlinear differential equations is realistic. Process DOEs based on system dynamics simulations are an inexpensive and effective way of gaining insights into sensitivity to interactions between process control variables. Monte Carlo simulations based on response surfaces are an effective way of assessing process robustness given the variations in the process control variables. Decisions based on probability of achieving certain objectives, given a certain level of variability in process parameters can reliably be made based on system dynamics and Monte Carlo simulations.