A fuzzy set approach for evaluating the achievability of an output time forecast in a wafer fabrication plant

Authors:
Toly Chen
Affiliations:
Department of Industrial Engineering and Systems Management, Feng Chia University, Taichung City, Taiwan
Venue:
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
Year:
2006

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Abstract

Lot output time prediction is a critical task to a wafer fab (fabrication plant). Traditional studies are focused on prediction accuracy and efficiency. Another performance measure that is as important but has been ignored in traditional studies is the achievability of an output time forecast, which is defined as the possibility that the fabrication on a wafer lot can be finished in time before the output time forecast. Theoretically, if a probability distribution can be obtained for the output time forecast, then the achievability can be evaluated with the cumulative probability of the probability distribution before the given date. However, there are many managerial actions that are more influential to the achievability. For this reason, a fuzzy set approach is proposed for evaluating the achievability of the output time forecast. The fuzzy set approach is composed of two parts: a fuzzy back propagation network (FBPN) and a set of fuzzy inference rules (FIRs). An example is used to demonstrate the applicability of the proposed methodology.