Model Predictive Control as a Simulator for Studying the Operation Quality of Semiconductor Supply Chains in the Perspective of Integrated Device Manufacturers

Abstract

The nature of competition in the semiconductor industry has shifted from inter-firm to inter-supply chain. For integrated device manufacturers (IDMs), effective supply chain management (SCM) has become their competitive advantage in the market with intensive rivalry. Model predictive control (MPC) is a convincingly robust and flexible technique for dynamically controlling material release, managing inventories, and meeting customer demand through supply chains. This study proposed an MPC framework for programming a nonstationary semiconductor manufacturing supply chain network in the perspective of IDMs. The supply chain network is characterized by multiple echelons from raw material supply to finished product shipment, multiple factories, manufacturing stochasticity, diverse product, and product substitution mechanisms. The MPC model was employed as a simulator to obtain the optimal operations of supply chain network under various combinations of three two-level scenario variables: high/low demand variation, push/pull supply chain strategy, and normal/quick raw material supply policy. The operation quality of supply chain and the effects of scenario variables were assessed based on multiple performance metrics.