Model Predictive Control (MPC) is presented as a robust, flexible decision framework for dynamically managing inventories and meeting customer demand in demand networks (a.k.a. supply chains). Ultimately, required safety stock levels in demand networks can be significantly reduced as a result ofthe performance demonstrated by the MPC approach. The translation ofavailable inf ormation in the supply chain problem into MPC variables is demonstrated with a two-node supply chain example. A six-node, two-product, threeechelon demand network problem proposed by Intel is well managed by a partially decentralized MPC implementation under simultaneous demand forecast inaccuracies and plant-model mismatch.
['Martin W. Braun', 'Daniel E. Rivera', 'W. Matthew Carlyle', 'Karl G. Kempf']
Application of Model Predictive Control to Robust Management of Multiechelon Demand Networks in Semiconductor Manufacturing