A novel optimization method to automated wet-etch station scheduling in semiconductor manufacturing systems

Abstract

This work addresses the short-term scheduling of one of the most critical stages in the semiconductor industry, the automated wet-etch station (AWS). An efficient MILP-based computer-aided tool is developed in order to achieve a proper synchronization between the activities of sequential chemical and water baths and limited automated wafer?s lot transfer devices. The major goal is to find the optimal integrated schedule that maximizes the whole process productivity without generating wafer contamination. Several examples are successfully solved to illustrate the capabilities of the proposed method.