Ant Colony Optimization Algorithm for Maintenance, Repair and Overhaul Scheduling Optimization in the Context of Industrie 4.0
Source abstract
Abstract
Maintenance, Repair, and Overhaul (MRO) is a crucial sector in the remanufacturing industry and scheduling of MRO processes is significantly different from conventional manufacturing processes. In this study, we adopted a swarm intelligent algorithm, Ant Colony Optimization (ACO), to solve the scheduling optimization of MRO processes with two business objectives: minimizing the total scheduling time (make-span) and total tardiness of all jobs. The algorithm also has the dynamic scheduling capability which can help the scheduler to cope with the changes in the shop floor which frequently occur in the MRO processes. Results from the developed algorithm have shown its better solution in comparison to commercial scheduling software. The dependency of the algorithm’s performance on tuning parameters has been investigated and an approach to shorten the convergence time of the algorithm is emerging.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Scheduling and Optimization Algorithms · Digital Transformation in Industry · Advanced Manufacturing and Logistics Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Smart Manufacturing Group, Advanced Remanufacturing and Technology Centre, A*STAR, Singapore 637143, Singapore
Funding
Advanced Manufacturing & Engineering (AME) Industry Alignment Funding
References (24)
Show source-provided references
1. Continuous maintenance and the future–Foundations and technological challenges10.1016/j.cirp.2016.06.006 ↗
2. Inspection scheduling based on reliability updating of gas turbine welded structures10.1177/1687814018819285 ↗
3. Coro, A., Macareno, L.M., Aguirrebeitia, J., and López de Lacalle, L.N. (2019). A Methodology to Evaluate the Reliability Impact of the Replacement of Welded Components by Additive Manufacturing Spare Parts. Metals, 9.10.3390/met9090932 ↗
4. Simulation Optimization for MRO Systems Operations10.1142/S0217595917500038 ↗
5. Production scheduling in flexible manufacturing systems: A state of the art survey
6. A survey of swarm intelligence for dynamic optimization: Algorithms and applications10.1016/j.swevo.2016.12.005 ↗
7. Ant colony optimization for unrelated parallel machine scheduling10.1007/s00170-013-4766-7 ↗
8. Huang, Z., Ding, J., Song, J., Shi, L., and Chen, C.H. (2016, January 14–17). Simulation optimization for the MRO scheduling problem based on multi-fidelity models. Proceedings of the 2016 IEEE International Conference on Industrial Technology (ICIT), Taipei, Taiwan.10.1109/ICIT.2016.7474992 ↗
9. Li, H., Mi, S., Li, Q., Wen, X., Qiao, D., and Luo, G. (2018). A scheduling optimization method for maintenance, repair and operations service resources of complex products. J. Intell. Manuf., 1–19.10.1007/s10845-018-1400-4 ↗
10. Visual computing as a key enabling technology for industrie 4.0 and industrial internet10.1109/MCG.2015.45 ↗
11. Dorigo, M., and Birattari, M. (2010). Ant Colony Optimization, Springer.10.1007/978-0-387-30164-8_22 ↗
12. Dorigo, M., and Stützle, T. (2019). Ant colony optimization: Overview and recent advances. Handbook of Metaheuristics, Springer.10.1007/978-3-319-91086-4_10 ↗
13. Implementation of an ant colony optimization technique for job shop scheduling problem10.1191/0142331206tm165oa ↗
14. Ant system: Optimization by a colony of cooperating agents10.1109/3477.484436 ↗
15. Ant system for job-shop scheduling
16. Literature review regarding Ant Colony Optimization applied to scheduling problems: Guidelines for implementation and directions for future research10.1016/j.engappai.2012.03.011 ↗
17. Zhuo, X.L., Zhang, J., and Cheng, W.N. (2007, January 25–28). A new pheromone design in ACS for solving JSP. Proceedings of the 2007 IEEE Congress on Evolutionary Computation, Singapore.10.1109/CEC.2007.4424714 ↗
18. Ant colony optimization for multi-objective flow shop scheduling problem10.1016/j.cie.2007.08.003 ↗
19. Flexible job shop scheduling problem using an improved ant colony optimization
20. An improved ant colony algorithm for dynamic hybrid flow shop scheduling with uncertain processing time10.1007/s10845-015-1144-3 ↗
21. Parallel processor scheduling for minimizing total weighted tardiness using ant colony optimization10.1007/s00170-008-1544-z ↗
22. Ant colony systems for the single-machine total weighted earliness tardiness scheduling problem10.1007/s10951-015-0429-x ↗
23. Enhancement of job shop scheduling with time windows using a wise select ant colony optimization
24. An event-driven integrative framework enabling information notification among manufacturing resources10.1080/0951192X.2019.1571232 ↗