Institute for Systems Research Technical Reports

This research aims at developing and implementing simulation-based operations research techniques to facilitate System Control (through sensitivity analysis) and System Design (through optimization) for semiconductor manufacturing systems.

Sensitivity analysis for small changes in input parameters is performed using gradient estimation techniques. Gradient estimation methods are evaluated by studying the state of the art and comparing the finite difference method and simultaneous perturbation method by applying them to a stochastic manufacturing system. The results are compared with the gradients obtained through analytical queueing models. The finite difference method is implemented in a heterogeneous simulation environment (HSE)-based decision support tool for process engineers. This tool performs heterogeneous simulations and sensitivity analyses.

The gradient-based techniques used for sensitivity analysis form the building blocks for a gradient-based discrete stochastic optimization procedure. This procedure is applied to the problem of allocating a limited budget to machine purchases to achieve throughput requirements and minimize cycle time. The performance of the algorithm is evaluated by applying the algorithm on a wide range of problem instances.

Reducing this time can reduce cycle time, reduce tool utilization, and increase tool capacity. This paper introduces the cluster tool scheduling problem for hybrid cluster tools, which are multiple-stage tools that have at least one stage with two or more parallel chambers.

This paper presents algorithms that can find superior sequences of wafer handler moves. Experimental results show that the tool performance can be improved significantly if the wafer handler follows a cyclic sequence instead of using a dispatching rule.

By monitoring the resonant frequency of exhaust process gases, the depletion of WF6 resulting from the reduction by H2 was readily observed in the 0.5 Torr process for wafer temperatures ranging from 300 to 350 C. Despite WF6 depletion rates as low as 3-5%, in-situ wafer-state metrology was achieved with an error less than 6% over 17 processed wafers.

This in-situ metrology capability combined with accurate sensor response modeling suggests an effective approach for acoustic process sensing in order to achieve run-to-run process control of the deposited tungsten film thickness.

The aim is to retrieve, for a new product design, a useful fixture from a given set of existing designs and their fixtures. Thus, the variant approach exploits this existing knowledge.

However, since calculating each fixture's feasibility and then determining the necessary modifications for infeasible fixtures would require too much effort, the approach searches quickly for the most promising fixtures based on a surrogate design similarity measure. Then, it evaluates the definitive usefulness metric for those promising fixtures and identifies the best one for the new design.