유전알고리즘 기반 로트 타겟팅 최적화 연구: 반도체 포토공정을 대상으로

Abstract

Production scheduling in a semiconductor wafer fabrication (FAB) can be decomposed into two phases: lot targeting and lot dispatching. A weighted dispatching rule is a widely applied concept to obtain the production schedule in the FAB under its complex manufacturing factors. The weights of the dispatching rule should be carefully determined since the weights substantially impact the performance of the FAB. In this study, we investigate a weighted lot targeting rule considering the time-variant manufacturing factors, i.e., processing times, set-up operations, work-in-process levels, and transportation times for the bottleneck (photolithography) process. We propose a Genetic Algorithm (GA) to determine the efficient weights of the weighted lot targeting rule within a limited simulation run. Our simulation experiments demonstrate that the proposed approach outperforms widely used targeting rules under the time-variant manufacturing factors in the FAB.