Hybrid discrete event simulation with model predictive control for semiconductor supply-chain manufacturing

Simulation modeling combined with decision control can offer important benefits for analysis, design, and operation of semiconductor supply-chain network systems. Detailed simulation of physical processes provides information for its controller to account for (expected) stochasticity present in the manufacturing processes. In turn, the controller can provide (near) optimal decisions for the operation of the processes and thus handle uncertainty in customer demands. In this paper, we describe an environment that synthesizes discrete-event system specification (DEVS) with model predictive control (MPC) paradigms using a knowledge interchange broker (KIB). This environment uses the KIB to compose discrete event simulation and model predictive control models. This approach to composability affords flexibility for studying semiconductor supply-chain manufacturing at varying levels of detail. We describe a hybrid DEVS/MPC environments via a knowledge interchange broker. We conclude with a comparison of this work with another that employs the Simulink/MATLAB environment.