Name
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.ejor.2009.12.026 | European Journal of Operational Research |
Keywords | Field | DocType |
Discrete event simulation,Response surface modeling,Design of experiments,Neural networks,Semiconductor manufacturing,Queueing | Black box (phreaking),Semiconductor device fabrication,Queueing theory,Throughput,Artificial neural network,Mathematics,Operations management,Metamodeling,Design of experiments,Discrete event simulation | Journal |
Volume | Issue | ISSN |
205 | 1 | 0377-2217 |
Citations | PageRank | References |
11 | 0.63 | 19 |
Authors | ||
1 | ||