A look-ahead fuzzy back propagation network for lot output time series prediction in a wafer fab

Authors:
Toly Chen
Affiliations:
Department of Industrial Engineering and Systems Management, Feng Chia University, Seatwen, Taichung City, Taiwan
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Year:
2006

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Abstract

Lot 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.