Semiconductor wafer fabrication involves possibly one of the most complex manufacturing processes ever used. This causes a number of decision problems. A successful system control strategy would assign appropriate decision rules for decision variables. Therefore, the goal of this study is to develop a scheduler for the selection of decision rules for decision variables in order to obtain the desired performance measures given by a user at the end of a certain production interval. In this proposed methodology, a system control strategy based on a simulation technique and a competitive neural network is suggested. A simulation experiment was conducted to collect the data containing the relationship between the change of decision rule set and current system status and the performance measures in the dynamic nature of semiconductor manufacturing fabrication. Then, a competitive neural network was applied to obtain the scheduling knowledge from the collected data. The results of the study indicate that applying this methodology to obtaining a control strategy is an effective method considering the complexity of semiconductor wafer fabrication systems.
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Min et al. (2003) studied this question.