Importance Sampling of Re-entrant Queueing Systems

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9622084 Deuermeyer This research focuses on the development of new simulation theory and methods to improve the performance and effectiveness of discrete simulation as it applies to semiconductor manufacturing. Planners and designers are becoming more interested in using cycle time to plan equipment purchases and scheduling policies; discrete-event simulation is the only analysis tool currently available to support design activities. Specific improvements in simulation methodology are needed for 1) faster execution speed, 2) methods to obtain cycle-time estimators, and 3)special variance-reduction technology that accounts for the increase in variability in cycle time caused by preventive maintenance and rare failure events. Generalized Semi-Markov Processes (GSMP) will be used as the modeling framework. This research will provide new capabilities in generating sample paths of GSMPs, developing importance sampling schemes for GSMPs, developing methods for computing crossing probabilities of cycle time and developing software to demonstrate the theoretical methods. These should contribute significantly toward solutions to the demanding problems in analysis and design of the extremely complex processes associated with semiconductor wafer fabs from the point of view of product cycle time and throughput rates, and facility and machine capacity.