Cluster tools have become an important tool type in the semiconductor industry during the last decade. They integrate several process chambers into a tool and enable sequential process steps within one tool and/or increase capacity and availability by using several chambers in parallel for the same step. In these cluster tools, several chambers are usually served by one robot. Different process times and the parallelism of the chambers lead to practically random and competing transport tasks and therefore to a dynamic sequence of events. Therefore a static capacity analysis is often insufficient and the deduction of improvement potentials requires complex analysis of the sequence of transport job executions. Besides external influences like the instant of the next delivery of a lot can change the ranking of different optimization criteria and temporarily favor a different sequencing rule. Commercially available simulation programs for semiconductor cluster tools are limited in the variety of sequencing rules and do not support such an analysis to the necessary extent.

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