TY - JOUR
T1 - Multilayer optimization and scheduling using model predictive control
T2 - Application to reentrant semiconductor manufacturing lines
AU - Vargas-Villamil, Felipe D.
AU - Rivera, Daniel
N1 - Funding Information:
We thank Dr K. Kempf of Intel Corporation for his advice and collaboration. We also thank Jose Flores-Godoy for his help with the implementation of the direct control layer. Financial support from the Mexican National Council for Science and Technology (CONACyT), the Institute of International Education (IIE), and the Intel Research Council is gratefully acknowledged.
Copyright:
Copyright 2007 Elsevier B.V., All rights reserved.
PY - 2000/9/1
Y1 - 2000/9/1
N2 - A two-layer production control method applied to discrete event reentrant semiconductor manufacturing lines is investigated. A modified l1-norm predictive controller/optimizer is proposed as a coordinator in the highest layer and a distributed control policy is used as a follow-up controller in the lowest layer. The use of a model predictive control (MPC) formulation allows the scheduling algorithm to simultaneously solve the production optimization and in-process inventory control problems at each sampling time. As an optimizer, the scheduler maximizes production rate and, as a controller, it addresses variability. Using this control-oriented framework, an optimal trade-off between production rate and cycle time is obtained. An l1-norm cost function allows the implementation of the optimization layer as a mixed integer linear program (MILP) which is solved at each time shift. The approach is applied to a one-product six-step, five-machine reentrant discrete event semiconductor manufacturing line whose specifications were provided by Intel Corporation. (C) 2000 Elsevier Science Ltd.
AB - A two-layer production control method applied to discrete event reentrant semiconductor manufacturing lines is investigated. A modified l1-norm predictive controller/optimizer is proposed as a coordinator in the highest layer and a distributed control policy is used as a follow-up controller in the lowest layer. The use of a model predictive control (MPC) formulation allows the scheduling algorithm to simultaneously solve the production optimization and in-process inventory control problems at each sampling time. As an optimizer, the scheduler maximizes production rate and, as a controller, it addresses variability. Using this control-oriented framework, an optimal trade-off between production rate and cycle time is obtained. An l1-norm cost function allows the implementation of the optimization layer as a mixed integer linear program (MILP) which is solved at each time shift. The approach is applied to a one-product six-step, five-machine reentrant discrete event semiconductor manufacturing line whose specifications were provided by Intel Corporation. (C) 2000 Elsevier Science Ltd.
KW - Discrete event system
KW - Hierarchical structure
KW - Model predictive control
KW - Reentrant manufacturing line
KW - Scheduling
KW - Semiconductor fabrication facility
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U2 - 10.1016/S0098-1354(00)00598-6
DO - 10.1016/S0098-1354(00)00598-6
M3 - Article
AN - SCOPUS:0034283808
SN - 0098-1354
VL - 24
SP - 2009
EP - 2021
JO - Computers and Chemical Engineering
JF - Computers and Chemical Engineering
IS - 8
ER -