The problem of reducing the mean and variance of cycle time in semiconductor manufacturing plants is addressed. Such plants feature a characteristic reentrant process flow, where lots repeatedly return at different stages of their production to the same service stations for further processing, consequently creating much competition for machines.We introduce a new class of scheduling policies, called Fluctuation Smoothing policies. Unanimously, our policies achieved the best mean cycle time and Standard Deviation of Cycle Time, in all the configurations of plant models and release policies tested. As an example, under the recommended Workload Regulation Release policy, for a heavily loaded Research and Development Fabrication Line model, our Fluctuation Smoothing policies achieved a reduction of 22.4% in the Mean Queueing Time, and a reduction of 52.0% in the Standard Deviation of Cycle Time, over the baseline FIFO policy.These conclusions are based on extensive simulations conducted on two models of semiconductor manufacturing plants. The first is a model of a Research and Development Fabrication Line that has been developed and studied earlier by Wein 111. The second is an aggregate model intended to approximate a full scale production line. Statistical tests are used to corroborate our conclusions.

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This paper discusses lane assignment on Automated Highway Systems(AHS) done to balance excess lane capacities . The lane assignment is formulated as a constrained optimization problem with the performance criterion being the balanced use of lanes. The optimization is done within the space of partitioned strategies. An algorithm for determining an o timal or suboptimal partitioned strate is developex The features of the developed a l g o r i t E are illustrated on an example of an AHS with 20 entry/exit points.