Metamodelling for cycle time-throughput-product mix surfaces using progressive model fitting

A meta-model based simulation optimization using hybrid simulation-analytical modeling to increase the productivity in automotive industry

“…In recent studies, Yang et al [34] proposed a simulation-based methodology to map the mean of steady-state cycle time (CT) as a function of throughput (TH) and product mix (PM) for manufacturing systems. In their study, a new meta-modeling methodology, coupled with preliminary queuing analysis, is proposed for generating the CT-TH-PM response surface via sequential simulation experiments.…”

Moving Least Squares Regression for High-Dimensional Stochastic Simulation Metamodeling

“…Stochastic simulation is often used to model complex systems to support decision making. For example, Yang et al [2011] use a simulation model of a semiconductor wafer fabrication system to estimate the expected throughput for any given scenario. Simulation runs may be time-consuming to execute, especially when many scenarios need to be investigated; for example, Tongarlak et al [2010] describe a simulation model of a fuel injector production line that takes 8h to run a single replication.…”

“…Simulation metamodeling allows the experimenter to obtain more benefits from a simulation because the simulation can be run when time is plentiful, and quick predictions can be made when decision-making time is scarce or expensive. Applications that need such metamodeling capability include manufacturing planning [Yang et al 2011] and financial security pricing [Liu and Staum 2010]. For instance, in manufacturing capacity or production planning, decision makers may want to consider trade-offs among system design and control parameters as they affect, say, throughput or cycle time.…”