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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.