A Novel Optimization Method to Automated Wet-Etch Station Scheduling in Semiconductor Manufacturing Systems

摘要

This work addresses the short-term scheduling of one of the most critical stages in thernsemiconductor industry, the automated wet-etch station (AWS). An efficient MILPbasedrncomputer-aided tool is developed in order to achieve a proper synchronizationrnbetween the activities of sequential chemical and water baths and limited automatedrnwafer’s lot transfer devices. The major goal is to find the optimal integrated schedulernthat maximizes the whole process productivity without generating wafer contamination.