A Look-Ahead Fuzzy Back Propagation Network for Lot Output Time Series Prediction in a Wafer Fab

Abstract

AbstractLot output time series is one of the most important time series data in a wafer fab (fabrication plant). Predicting the output time of every lot is therefore a critical task to the wafer fab. To further enhance the effectives and efficiency of wafer lot output time prediction, a look-ahead fuzzy back propagation network (FBPN) is constructed in this study with two advanced features: the future release plan of the fab is considered (look-ahead); expert opinions are incorporated. Production simulation is also applied in this study to generate test examples. According to experimental results, the prediction accuracy of the look-ahead FBPN was significantly better than those of four existing approaches: multiple-factor linear combination (MFLC), BPN, case-based reasoning (CBR), and FBPN without look-ahead, by achieving a 12%~37% (and an average of 19%) reduction in the root-mean-squared-error (RMSE) over the comparison basis – MFLC.KeywordsRoot Mean Square ErrorFuzzy NumberCase Base ReasoningOutput TimeWafer FabricationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.