Metaheuristic scheduling of 300-mm lots containing multiple orders

The standard unit of transfer in new semiconductor wafer fabrication facilities is the front opening unified pod (FOUP). Due to automated material handling system concerns, the number of FOUPs in a wafer fab is kept limited. Moreover, a certain number of new and larger 300-mm wafers will be placed in these FOUPs and this makes grouping orders from multiple customers into a job a necessity. Thereby, efficient utilization of the FOUP capacity while attaining good system performance is a challenge. We previously investigated optimization-based solution approaches for minimizing total weighted completion time and maximizing on-time delivery performance for the single machine multiple orders per job scheduling problem. We present two metaheuristic solution approaches for this scheduling problem under two different typical wafer fab machine environments: single unit processing and single lot processing. Experimental results demonstrate that the metaheuristic approaches can find near-optimal solutions for realistic-sized 300-mm scheduling problems in an acceptable amount of computation time.

[1]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[2]  Hong Zhou,et al.  Using Genetic Algorithms and Heuristics for Job Shop Scheduling with Sequence-Dependent Setup Times , 2001, Ann. Oper. Res..

[3]  P. Aravindan,et al.  Comparative evaluation of genetic algorithms for job-shop scheduling , 2001 .

[4]  Robert C. Leachman,et al.  Special Issue: Franz Edelman Award for Achievement in Operations Research and the Management Sciences: SLIM: Short Cycle Time and Low Inventory in Manufacturing at Samsung Electronics , 2002, Interfaces.

[5]  Emanuel Falkenauer,et al.  A genetic algorithm for job shop , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[6]  John W. Fowler,et al.  The single machine multiple orders per job scheduling problem , 2004 .

[7]  K. Dejong,et al.  An analysis of the behavior of a class of genetic adaptive systems , 1975 .

[8]  Gerald M. Knapp,et al.  Multiple setup PCB assembly planning using genetic algorithms , 2002 .

[9]  R. Stephenson A and V , 1962, The British journal of ophthalmology.

[10]  Salvatore Cavalieri,et al.  A genetic algorithm for job-shop scheduling in a semiconductor manufacturing system , 1999, IECON'99. Conference Proceedings. 25th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.99CH37029).

[11]  N. Jawahar,et al.  A multiobjective genetic algorithm for job shop scheduling , 2001 .