지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- Korean Society for Precision Engineering Journal of the Korean Society for Precision Engineering Journal of the Korean Society for Precision Engineering Vol.40 No.2
- 발행연도
- 2023.2
- 수록면
- 163 - 173 (11page)
- DOI
- 10.7736/JKSPE.022.100
이용수
초록· 키워드
오류제보하기
In the scheduling of assembly lines with human-robot collaboration, variations in workload caused by differences in the available working hours of workers and robots must be minimized. A scheduling method that considers buffers shared by automated guided vehicles and cooperative assembly by multiple workers is proposed herein. In particular, cooperative work requires an assembly schedule that minimizes the make span and satisfies the delivery date, while accounting for the possibility of work partitioning, the number of workers, as well as their available time slots and skills. Hence, it is difficult to obtain an exact optimal solution within a reasonable computation time using existing methods such as mathematical programming. Heuristic or metaheuristic approaches are effective for solving this problem. However, these approaches are not suitable for cooperative assembly by multiple workers. Therefore, a genetic algorithm supported by dispatching rules with four genes is proposed. Computational experiments are conducted based on multiple worker skills. The results showed that when the worker skills are the same, the genetic representation of the job name and part processing order is effective, whereas when the worker skills are different, the genetic representation of the cooperative process with the worker for each operation is effective.
목차
1. Introduction
2. Scheduling Problem Setting
3. Scheduling Method based on GENETIC Algorithm
4. Evaluation Experiment
5. Conclusion
REFERENCES
참고문헌 (13)
참고문헌 신청
Borreguero-Sanchidrián, T., Pulido, R., García-Sánchez, Á., Ortega-Mier, M., (2017), Flexible job shop scheduling with operators in aeronautical manufacturing: A case study, IEEE Access, 6, 224-233.
Chen, C., Tiong, L. K., Chen, I.-M., (2019), Using a genetic algorithm to schedule the space-constrained AGV-based prefabricated bathroom units manufacturing system, International Journal of Production Research, 57(10), 3003-3019.
Elmi, A., Topaloglu, S., (2013), A scheduling problem in blocking hybrid flow shop robotic cells with multiple robots, Computers & Operations Research, 40(10), 2543-2555.
Fu, G., (2004), A method for solving jobshop scheduling problems with limited common buffers, transactions of the institute of systems, Control and Information Engineers, 17(3), 113-121. Japanese
Gong, G., Deng, Q., Gong, X., Liu, W., Ren, Q., (2018), A new double flexible job-shop scheduling problem integrating processing time, green production, and human factor indicators, Journal of Cleaner Production, 174, 560-576.
Chen, C., Tiong, L. K., Chen, I.-M., (2019), Using a genetic algorithm to schedule the space-constrained AGV-based prefabricated bathroom units manufacturing system, International Journal of Production Research, 57(10), 3003-3019.
Elmi, A., Topaloglu, S., (2013), A scheduling problem in blocking hybrid flow shop robotic cells with multiple robots, Computers & Operations Research, 40(10), 2543-2555.
Fu, G., (2004), A method for solving jobshop scheduling problems with limited common buffers, transactions of the institute of systems, Control and Information Engineers, 17(3), 113-121. Japanese
Gong, G., Deng, Q., Gong, X., Liu, W., Ren, Q., (2018), A new double flexible job-shop scheduling problem integrating processing time, green production, and human factor indicators, Journal of Cleaner Production, 174, 560-576.
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