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A joint optimization model of maintenance and operation of high-speed train fleets is established with the optimization objective of minimizing the total costs, considering dynamic passenger flow and maintenance resources. A new maintenance strategy CCPM (Coordinating Conflicts Preventive Maintenance) is proposed to optimize the problem. The effectiveness of the model and the strategy are verified by numerical examples. The comparison between the strategy in the paper and the existing approach proves that the new strategy is more effective and shows the importance of considering dynamic passenger flow. The model and the strategy provide decision support for the actual high-speed trains operation and maintenance program. This study also offers new ideas to the subsequent research on preventive maintenance of high-speed trains.
Czasopismo
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Tom
Strony
297--305
Opis fizyczny
Bibliogr. 34 poz., rys., tab.
Twórcy
autor
- Shanghai Jiao Tong University, Shanghai, 200240, China
autor
- Shanghai Jiao Tong University, Shanghai, 200240, China
autor
- Wenzhou University, Wenzhou, 325035, China
Bibliografia
- 1. An Y,Chen X,Hu J, et al. Joint optimization of preventive maintenance and production rescheduling with new machine insertion andprocessing speed selection. Reliability Engineering & System Safety 2022; 108269, https://doi.org/10.1016/j.ress.2021.108269.
- 2. Berrichi A,Yalaoui F,Amodeo L, et al. Bi-objective ant colony optimization approach to optimize production and maintenance scheduling. Computers & Operations Research 2010; 37(9): 1584-1596, https://doi.org/10.1016/j.cor.2009.11.017
- 3. Berrichi A,Amodeo L,Yalaoui F, et al. Bi-objective optimization algorithms for joint production and maintenance scheduling: Application to the parallel machine problem. Journal of Intelligent Manufacturing 2009; 20(4): 389, https://doi.org/10.1016/j.cor.2020.104943.
- 4. Cheng G,Li L. Joint optimization of production, quality control and maintenance for serial-parallel multistage production systems. Reliability Engineering & System Safety 2020; 204: 107146, https://doi.org/10.1016/j.ress.2020.107146.
- 5. Cheung K Y,Hui C W,Sakamoto H, et al. Short-term site-wide maintenance scheduling. Computers & chemical engineering 2004; 28(1-2): 91-102, https://doi.org/10.1016/S0098-1354(03)00177-7.
- 6. De Jonge B,Scarf P A. A review on maintenance optimization. European journal of operational research 2020; 285(3): 805-824, https://doi.org/10.1016/j.ejor.2019.09.047.
- 7. Fakher H B,Nourelfath M,Gendreau M. Integrating production, maintenance and quality: A multi-period multi-product profit-maximization model. Reliability Engineering & System Safety 2018; 170: 191-201, https://doi.org/10.1016/j.ress.2017.10.024.
- 8. Geng L,Lu R,Li X. Predicting intercity high-speed railway passenger flow based on volatility clustering. Journal of Railway Science and Engineering 2019; 16(08): 1890-1896, http://dx.doi.org/10.19713/j.cnki.43-1423/u.2019.08.004.
- 9. Giacco G L,D’ariano A,Pacciarelli D. Rolling stock rostering optimization under maintenance constraints. Journal of Intelligent Transportation Systems 2014; 18(1): 95-105, https://doi.org/10.1080/15472450.2013.801712.
- 10. Gu H,Lam H C. A genetic algorithm approach for scheduling trains maintenance under uncertainty. International Conference on Computer Science, Applied Mathematics and Applications. 2019; 106-118, https://doi.org/10.1007/978-3-030-38364-0_10.
- 11. Hadidi L A,Al Turki U M,Rahim A. Integrated models in production planning and scheduling, maintenance and quality: A review. International Journal of Industrial and Systems Engineering 2012; 10(1): 21-50, https://doi.org/10.1007/978-1-4615-1635-4_1.
- 12. Hu J,Jiang Z,Liao H. Preventive maintenance of a single machine system working under piecewise constant operating condition. Reliability Engineering & System Safety 2017; 168: 105-115, https://doi.org/10.1016/j.ress.2017.05.014.
- 13. Jafar-Zanjani H,Zandieh M,Sharifi M. Robust and resilient joint periodic maintenance planning and scheduling in a multi-factory network under uncertainty: A case study. Reliability Engineering & System Safety 2022; 217: 108113, https://doi.org/10.1016/j.ress.2021.108113.
- 14. Kang R,Wang J,Cheng J, et al. Intelligent forecasting of automatic train protection system failure rate in china high-speed railway. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2019; 21(4), http://dx.doi.org/10.17531/ein.2019.4.5.
- 15. Kuo Y,Chang Z A. Integrated production scheduling and preventive maintenance planning for a single machine under a cumulative damage failure process. Naval Research Logistics (NRL) 2007; 54(6): 602-614, https://doi.org/10.1002/nav.20232.
- 16. Lai Y C,Fan D C,Huang K L. Optimizing rolling stock assignment and maintenance plan for passenger railway operations. Computers & Industrial Engineering 2015; 85: 284-295, https://doi.org/10.1016/j.cie.2015.03.016.
- 17. Lin B,Wu J,Lin R, et al. Optimization of high-level preventive maintenance scheduling for high-speed trains. Reliability Engineering & System Safety 2019; 183: 261-275, https://doi.org/10.1016/j.ress.2018.11.028.
- 18. Linnéusson G,Ng A H,Aslam T. A hybrid simulation-based optimization framework supporting strategic maintenance development to improve production performance. European Journal of Operational Research 2020; 281(2): 402-414, https://doi.org/10.1016/j.ejor.2019.08.036.
- 19. Liu X,Wang W,Peng R. An integrated production and delay-time based preventive maintenance planning model for a multi-product production system. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2015; 17(2): 215--221, http://dx.doi.org/10.17531/ein.2015.2.7.
- 20. Lotovskyi E,Teixeira A P,Soares Guedes C. Availability analysis of an offshore oil and gas production system subjected to age-based preventive maintenance by petri nets. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2020; 22(4), http://dx.doi.org/10.17531/ein.2020.4.6.
- 21. Luan X,Miao J,Meng L, et al. Integrated optimization on train scheduling and preventive maintenance time slots planning. Transportation Research Part C: Emerging Technologies 2017; 80: 329-359, https://doi.org/10.1016/j.trc.2017.04.010
- 22. Naderi B,Zandieh M,Ghomi S F. Scheduling sequence-dependent setup time job shops with preventive maintenance. The International Journal of Advanced Manufacturing Technology 2009; 43(1-2): 170, https://doi.org/10.1007/s00170-008-1693-0.
- 23. Najid N M,Alaoui Selsouli M,Mohafid A. An integrated production and maintenance planning model with time windows and shortage cos International journal of production research 2011; 49(8): 2265-2283, https://doi.org/10.1080/00207541003620386.
- 24. Pandey D,Kulkarni M S,Vrat P. Joint consideration of production scheduling, maintenance and quality policies: A review and conceptual framework. International Journal of Advanced Operations Management 2010; 2(1-2): 1-24, https://doi.org/10.1504/ijaom.2010.034583.
- 25. Peng H,Van Houtum G-J. Joint optimization of condition-based maintenance and production lot-sizing. European Journal of Operational Research 2016; 253(1): 94-107, https://doi.org/10.1016/j.ejor.2016.02.027.
- 26. Polotski V,Kenne J-P,Gharbi A. Joint production and maintenance optimization in flexible hybrid manufacturing–remanufacturing systems under age-dependent deterioration. International Journal of Production Economics 2019; 216: 239-254, https://doi.org/10.1016/j.ijpe.2019.04.023.
- 27. Škerlič S,Sokolovskij E,Erčulj V. Maintenance of heavy trucks: An international study on truck drivers. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2020; 22(3), http://dx.doi.org/10.17531/ein.2020.3.12.
- 28. Uit Het Broek M A,Teunter R H,De Jonge B, et al. Joint condition-based maintenance and condition-based production optimization. Reliability Engineering & System Safety 2021; 214: 107743, https://doi.org/10.1016/j.ress.2021.107743.
- 29. Wang H,Yang G,He Y. Preventive maintenance decision for emu component considering passenger flow distribution. Computer Integrated Manufacturing Systems 2020; 1-13.
- 30. Wang J,Zhao Y,Gronalt M, et al. Synchronized optimization for service scheduling, train parking and routing at high-speed rail maintenance depot. IEEE Transactions on Intelligent Transportation Systems 2021, https://doi.org/10.1109/TITS.2020.3045852.
- 31. Yan S,Ma B,Wang X, et al. Maintenance policy for oil-lubricated systems with oil analysis data. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2020; 22(3), http://dx.doi.org/10.17531/ein.2020.3.8.
- 32. Yang H,Li W,Wang B. Joint optimization of preventive maintenance and production scheduling for multi-state production systems based on reinforcement learning. Reliability Engineering & System Safety 2021; 214: 107713, https://doi.org/10.1016/j.ress.2021.107713.
- 33. Zhang Y,D’ariano A,He B, et al. Microscopic optimization model and algorithm for integrating train timetabling and track maintenance task scheduling. Transportation Research Part B: Methodological 2019; 127: 237-278, https://doi.org/10.1016/j.trb.2019.07.010.
- 34. Zhong Q,Lusby R M,Larsen J, et al. Rolling stock scheduling with maintenance requirements at the chinese high-speed railway. Transportation Research Part B: Methodological 2019; 126: 24-44, https://doi.org/10.1016/j.trb.2019. 05.013.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-40f1d874-89e3-4193-ae6f-2cbe5b101a11