A model predictive control approach for real-time optimization of reentrant manufacturing lines

A two layer hierarchical framework for optimization, control, and schedulin g of semi-conductor reentrant lines is proposed. In this framework, model p redictive control (MPC) is used at the top layer for real-time optimization (RTO). This layer acts as an interface between long-term planning (months) and scheduling (minutes). An l(1)-norm MPC, which uses a discrete linear m odel, addresses the long-term (shifts) inventory control problem while mini mizing cycle time. It can also address the inventory and production control problems. The receding horizon feature of MPC allows the algorithm to simu ltaneously act as a long-term optimizer and as a controller. This algorithm is implemented as a linear programming (LP) problem, which is solved at th e beginning of each shift. At the lower level, a variable priority policy ( VPP) tracks the commands generated by the optimizer/controller providing th e detailed operation of the discrete event fabrication line. The approach i s illustrated with a case study of a five-machine, six-step line example de veloped by Intel. (C) 2001 Elsevier Science B.V. All rights reserved.