TY - JOUR
T1 - Batch production scheduling for semiconductor back-end operations
AU - Fu, Mengying
AU - Askin, Ronald
AU - Fowler, John
AU - Haghnevis, Moeed
AU - Keng, Naiping
AU - Pettinato, Jeffrey S.
AU - Zhang, Muhong
N1 - Funding Information:
Dr. Askin is a Fellow of IIE and has published extensively. His list of awards includes the National Science Foundation Presidential Young Investigator Award, the Shingo Prize for Excellence in Manufacturing Research, the IIE Joint Publishers Book of the Year Award, and the IIE Transactions Development and Applications Award.
PY - 2011/5
Y1 - 2011/5
N2 - A good production schedule in a semiconductor back-end facility is critical for the on time delivery of customer orders. However, the scheduling process is usually difficult due to the wide product mix, large number of parallel machines, product family-related setups, and high weekly demand consisting of thousands of lots. In this paper, we present a new mixed-integer-linear- programming (MILP) model for the batch production scheduling of a semiconductor back-end facility with serial production stages. Computational results are provided for finding optimal solutions to small problem instances. Due to the limitation on the solvable size of the MILP formulation, a deterministic scheduling system (DSS), including an optimizer and a scheduler, is proposed to provide suboptimal solutions in a reasonable time for large real-world problem instances. Small problem instances are randomly generated to compare the performances of the optimization model and the DSS. An experimental design is utilized to understand the behavior of the DSS under different production scenarios.
AB - A good production schedule in a semiconductor back-end facility is critical for the on time delivery of customer orders. However, the scheduling process is usually difficult due to the wide product mix, large number of parallel machines, product family-related setups, and high weekly demand consisting of thousands of lots. In this paper, we present a new mixed-integer-linear- programming (MILP) model for the batch production scheduling of a semiconductor back-end facility with serial production stages. Computational results are provided for finding optimal solutions to small problem instances. Due to the limitation on the solvable size of the MILP formulation, a deterministic scheduling system (DSS), including an optimizer and a scheduler, is proposed to provide suboptimal solutions in a reasonable time for large real-world problem instances. Small problem instances are randomly generated to compare the performances of the optimization model and the DSS. An experimental design is utilized to understand the behavior of the DSS under different production scenarios.
KW - Heuristic
KW - mixed integer linear programming
KW - scheduling
KW - semiconductor back-end
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U2 - 10.1109/TSM.2011.2114900
DO - 10.1109/TSM.2011.2114900
M3 - Article
AN - SCOPUS:79955653428
SN - 0894-6507
VL - 24
SP - 249
EP - 260
JO - IEEE Transactions on Semiconductor Manufacturing
JF - IEEE Transactions on Semiconductor Manufacturing
IS - 2
M1 - 5752257
ER -