Institute for Systems Research Technical Reports

Permanent URI for this collectionhttp://hdl.handle.net/1903/4376

This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.

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Author: search.filters.author.Herrmann, Jeffrey W.Subject: search.filters.subject.semiconductor manufacturing

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    Sequencing Wafer Handler Moves to Improve the Performance of Sequential Cluster Tools
    (2000) Herrmann, Jeffrey W.; Nguyen, Manh-Quan T.; ISR
    Cluster tools are highly integrated machines that can perform a sequence of semiconductor manufacturing processes. The sequence of wafer handler moves affects the total time needed to process a set of wafers. Reducing this time can reduce cycle time, reduce tool utilization, and increase tool capacity. This paper introduces the cluster tool scheduling problem for sequential cluster tools and describes a branch-and-bound algorithm that can find an optimal sequence of wafer handler moves. In addition, we enumerate the set of 1-unit cyclic sequences for two- and three-stage sequential cluster tools. 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.
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    Evaluating the Impact of Process Changes on Cluster Tool Performance
    (1999) Herrmann, Jeffrey W.; Chandrasekaran, Niranjan; Conaghan, Brian F.; Nguyen, Manh-Quan; Rubloff, Gary W.; Shi, Rock Z.; ISR
    Cluster tools are highly integrated machines that can perform a sequence of semiconductor manufacturing processes. Their integrated nature can complicate analysis when evaluating how process changes affect the overall tool performance.

    This paper presents two integrated models for understanding cluster tool behavior. The first model is a network model that evaluates the total lot processing time for a given sequence of activities. By including a manufacturing process model (in the form of a response surface model, or RSM), the model calculates the total lot processing time as a function of the process parameter values and other operation times. This model allows one to quantify the sensitivity of total lot processing time with respect to process parameters and times.

    In addition, we present an integrated simulation model that includes a process model. For a given scheduling rule that the cluster tool uses to sequence wafer movements, one can use the simulation to evaluate the impact of process changes including changes to product characteristics and changes to process parameter values. In addition, one can construct an integrated network model to quantify the sensitivity of total lot processing time with respect to process times and process parameters in a specific scenario.

    The examples presented here illustrate the types of insights that one can gain from using such methods. Namely, the total lot processing time is a function not simply of each operation's process time, but specifically of the chosen process parameter values. Modifying the process parameter values may have significant impacts on the manufacturing system performance, a consequence of importance which is not readily obvious to a process engineer when tuning a process (though in some cases, reducing process times may not change the total lot processing time much).

    Additionally, since the cluster tool's maximum throughput depends upon the process parameters, the tradeoffs between process performance and throughput should be considered when evaluating potential process changes and their manufacturing impact.