Development of a real -time multiobjective scheduler for semiconductor fabrication systems

Semiconductor wafer fabrication involves perhaps the most complex manufacturing process 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 was to develop a scheduler for selection of decision rules for decision variables in order to obtain 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 change of decision rule set and current system status and performance measures in the dynamic nature of semiconductor manufacturing fab. Then, the competitive neural network was applied to obtain the scheduling knowledge from the collected data. The results of this study indicate that applying this methodology to obtaining a control strategy is an effective method with the complexity of semiconductor wafer fabrication systems