A simulation-based methodology is proposed to map the mean of steady-state cycle time (CT) as a function of throughput (TH) and product mix (PM) for manufacturing systems. Nonlinear regression models motivated by queueing analysis are assumed for the underlying response surface. To ensure efficiency and control estimation error, simulation experiments are built up sequentially using a multi-stage procedure to collect data for fitting the models. The resulting response surface is able to provide a CT estimate for any TH and any PM, and thus allows the decision maker to instantly investigate options and trade offs regarding their production planning.