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Neural network metamodeling for cycle time-throughput profiles in manufacturing

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  • Yang, Feng
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    Abstract

    This paper proposed a neural network (NN) metamodeling method to generate the cycle time (CT)-throughput (TH) profiles for single/multi-product manufacturing environments. Such CT-TH profiles illustrate the trade-off relationship between CT and TH, the two critical performance measures, and hence provide a comprehensive performance evaluation of a manufacturing system. The proposed methods distinct from the existing NN metamodeling work in three major aspects: First, instead of treating an NN as a black box, the geometry of NN is examined and utilized; second, a progressive model-fitting strategy is developed to obtain the simplest-structured NN that is adequate to capture the CT-TH relationship; third, an experiment design method, particularly suitable to NN modeling, is developed to sequentially collect simulation data for the efficient estimation of the NN models.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 205 (2010)
    Issue (Month): 1 (August)
    Pages: 172-185

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    Handle: RePEc:eee:ejores:v:205:y:2010:i:1:p:172-185

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    Web page: http://www.elsevier.com/locate/eor

    Related research

    Keywords: Discrete event simulation Response surface modeling Design of experiments Neural networks Semiconductor manufacturing Queueing;

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