Using simulation and genetic algorithms to improve cluster tool performance

Cluster tools have gained importance in the fabrication of semiconductor chips. In this paper, we present an approach to generate optimal processing sequences of lots using cluster tools. We consider the problem of sequencing n lots, where each lot can be processed by any of m available cluster tools. The proposed method combines simulation and a genetic algorithm to generate lot processing sequences. We show that our approach leads to a significant reduction of the cycle times of the cluster tools.

[1]  John L. Mauer,et al.  The simulation of integrated tool performance in semiconductor manufacturing , 1993, WSC '93.

[2]  Robert W. Atherton,et al.  Performance analysis of multi-process semiconductor manufacturing equipment , 1990, IEEE/SEMI Conference on Advanced Semiconductor Manufacturing Workshop.

[3]  Todd LeBaron,et al.  The simulation of cluster tools: a new semiconductor manufacturing technology , 1994, Proceedings of Winter Simulation Conference.

[4]  S. Venkatesh,et al.  A steady-state throughput analysis of cluster tools: dual-blade versus single-blade robots , 1997 .

[5]  John L. Mauer,et al.  Using simulation to analyze integrated tool performance in semiconductor manufacturing , 1994 .

[6]  R. S. Gyurcsik,et al.  Single-wafer cluster tool performance: an analysis of throughput , 1994 .

[7]  R. S. Gyurcsik,et al.  Single-wafer cluster tool performance: an analysis of the effects of redundant chambers and revisitation sequences on throughput , 1996 .

[8]  S. C. Wood,et al.  Simple performance models for integrated processing tools , 1996 .

[9]  Tae-Eog Lee,et al.  Performance Modeling of Cluster Tools using Timed Petri Nets , 1999 .

[10]  S. C. Wood,et al.  A generic model for cluster tool throughput time and capacity , 1994, Proceedings of 1994 IEEE/SEMI Advanced Semiconductor Manufacturing Conference and Workshop (ASMC).

[11]  Neal G. Pierce,et al.  Development of generic simulation models to evaluate wafer fabrication cluster tools , 1992, WSC '92.

[12]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .