Sensitivity search for the rescheduling of semiconductor photolithography operations

This study deals with the rescheduling problem of the photolithography area in semiconductor wafer fabrications. The objective is to find a schedule that minimizes the weighted sum of makespan, maximum tardiness, and total setup time. Practical issues such as machine breakdowns, limited number of available masks, restrictions on photoresist, production notice, and machine setup are considered. Three popular search algorithms—simulated annealing (SA), genetic algorithm (GA), and tabu search (TS) — are tested to solve the scheduling problem. We also propose a new sensitivity search approach. A new event changes the scheduling problem. Thus, the problem needs to be re-solved to reflect such changes. In an actual production environment, we propose that, instead of searching for a solution from scratch, the search process can be restarted from the best solution of an original problem that is very similar to the new problem. Using an industrial data set, this study tests the proposed approach. The results show that TS performs the best among the algorithms tested, and the performance of the sensitivity TS significantly surpasses that of the traditional approach.