자동화 물류시스템 내 차량 혼잡도를 고려한 무인운반차량의 동적 경로 결정 알고리즘

• 영문명: A Dynamic OHT Routing Algorithm in Automated Material Handling Systems
• 발행기관: 한국산업경영시스템학회
• 저자명: 강봉권(Bonggwon Kang) 강병민(Byeong Min Kang) 홍순도(Soondo Hong)
• 간행물 정보: 『산업경영시스템학회지』제45권 제3호, 40~48쪽, 전체 9쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2022.09.30

영문 초록

An automated material handling system (AMHS) has been emerging as an important factor in the semiconductor wafer manu- facturing industry. In general, an automated guided vehicle (AGV) in the Fab’s AMHS travels hundreds of miles on guided paths to transport a lot through hundreds of operations. The AMHS aims to transfer wafers while ensuring a short delivery time and high operational reliability. Many linear and analytic approaches have evaluated and improved the performance of the AMHS under a deterministic environment. However, the analytic approaches cannot consider a non-linear, non-convex, and black-box performance measurement of the AMHS owing to the AMHS’s complexity and uncertainty. Unexpected vehicle con- gestion increases the delivery time and deteriorates the Fab’s production efficiency. In this study, we propose a Q-Learning based dynamic routing algorithm considering vehicle congestion to reduce the delivery time. The proposed algorithm captures time-variant vehicle traffic and decreases vehicle congestion. Through simulation experiments, we confirm that the proposed algorithm finds an efficient path for the vehicles compared to benchmark algorithms with a reduced mean and decreased standard deviation of the delivery time in the Fab’s AMHS.

목차

1. 서 론

2. 문헌연구

3. 반도체 자동화 물류시스템

4. 정체경로 우회 위한 동적 경로 결정

5. 시뮬레이션 실험

6. 결 론

키워드

Dynamic Routing Q-Learning Automated Material Handling System Simulation