Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Simulation optimization using metamodels
Winter Simulation Conference
The influence of correlation functions on stochastic kriging metamodels
Proceedings of the Winter Simulation Conference
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A simulation-based methodology is proposed to map the mean of steady-state cycle time as a function of throughput and product mix for manufacturing systems. Nonlinear regression models motivated by queueing analysis are assumed for the underlying response surface. To insure efficiency and control estimation error, simulation experiments are built up sequentially using a multistage procedure to collect data for the fitting of the models. The resulting response surface is able to provide a cycle-time estimate for any throughput and any product mix, and thus allows the decision maker to instantly investigate options and trade offs regarding their production planning.