A New Approach to On-Line Rescheduling for a Semiconductor Foundry Fab

Production scheduling is a complex task in most real manufacturing settings and semiconductor manufacturing is no exception. To control such complex systems, it is a challenge to determine appropriate dispatching strategies under various system conditions. Therefore, dispatching strategies are important to improve the system performance, especially for the real time control of the system. In this paper, an on-line rescheduling mechanism combined with theory of constraints (TOC) is proposed. Genetic algorithm (GA) is for searching dispatching rule sets which promote better performance. With system conditions corresponding to dispatching rules, the support vector machine (SVM) classifier is constructed as the scheduler. Also, the adaptive neuro-fuzzy inference system (ANFIS) prediction model is built for the sake of on-line deciding the scheduling intervals. The results indicate that applying the proposed mechanism to obtaining dispatching strategies is an effective method dealing the product mix problem and considering the complexity and variation of semiconductor wafer fabrication systems.