Joint optimization of condition-based maintenance policy and buffer capacity for a two-component self-repairable serial system

• Autorzy: Meng Yinghao , Lin Mengmeng , Xu Zihao , Yin Zhen

Identyfikatory

DOI

10.17531/ein/185581

• Języki publikacji: EN

Abstrakty

EN

This paper investigates a self-repairable serial system with two components and a buffer. Competitive failure processes are considered due to the internal degradation and external shock processes of components. The system reliability is calculated based onthe integration of the internal degradation process and external shock process. When one of the components deteriorates to the PM or CM thresholds, it is restored to an imperfect state under dynamic time limitationsbased on the previous internal degradation and external shocks.As for the other component, it needs to be repaired or not according to the reliability of the component; it needs to be shut down or not based on the buffer status and the allocation of the component in the system.The optimal initial buffer capacity setting and PM threshold at minimum cost are found by minimizing the system's total cost in a given running cycle. Finally, numerical and case studies are provided to demonstratethe feasibility and superiority of the presented model.

Słowa kluczowe

EN

self-repairable serial system; competitive failure; buffer capacity; degradation process; external shock process

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2024
• Tom: Vol. 26, no. 2
• Strony: art. no. 185581
• Opis fizyczny: Bibliogr. 33 poz., rys., tab., wykr.

Twórcy

autor

Meng Yinghao

• Wenzhou University, China

• https://orcid.org/0009-0004-5232-8769

autor

Lin Mengmeng

• Wenzhou University, China

• https://orcid.org/0000-0003-4406-7322

autor

Xu Zihao

• Wenzhou University, China

autor

Yin Zhen

• Wenzhou University, China

Bibliografia

• 1. E G Kyriakidis, T D Dimitrakos. Optimal preventive maintenance of a production system with an intermediate buffer[J]. European Journal of Operational Research,2004,168(01):86-99. https://doi.org/10.1016/j.ejor.2004.01.052.
• 2. C C Karamatsoukis, E G Kyriakidis. Optimal maintenance of two stochastically deteriorating machines with an intermediate buffer[J]. European Journal of Operational Research,2010,207(01):297-308. https://doi.org/10.1016/j.ejor.2010.04.022.
• 3. L Wang, Z Q Lu, Y J Zhang. Joint optimisation of maintenance planning and buffer allocation for serial production systems[J]. Computer Integrated Manufacturing Systems,2016,22(05):1296-1304.http://www.cims-journal.cn/CN/10.13196/j.cims.2016.05.016.
• 4. M C Fitouhi, M Nourelfath, S B. Gershwin. Performance evaluation of a two-machine line with a finite buffer and condition-based maintenance[J]. Reliability Engineering and System Safety,2017,166:61-72. https://doi.org/10.1016/j.ress.2017.03.034.
• 5. N Zhang, F Q Qi, C J Zhang, et al. Joint optimization of condition-based maintenance policy and buffer capacity for a two-unit series system[J]. Reliability Engineering and System Safety,2022,219. https://doi.org/10.1016/j.ress.2021.108232.
• 6. S C Wei, M Nourelfath, N Nahas. Analysis of a production line subject to degradation and preventive maintenance[J]. Reliability Engineering and System Safety,2023,230. https://doi.org/10.1016/j.ress.2022.108906.
• 7. S Y Gan, N Shen. Maintenance Optimization for a Production System Subject to Shocks Considering a Buffer Inventory and Production Defects[J]. Reliability Engineering and System Safety,2023,238. https://doi.org/10.1016/j.ress.2023.109487.
• 8. X J Zhou, C J Wu, Y T Li, et al. A preventive maintenance model for leased equipment subject to internal degradation and external shock damage[J]. Reliability Engineering and System Safety,2016,154. https://doi.org/10.1016/j.ress.2016.05.005.
• 9. L Yang, X B Ma, Y Zhao. A condition-based maintenance model for a three-state system subject to degradation and environmental shocks[J]. Computers & Industrial Engineering,2017,105. https://doi.org/10.1016/j.cie.2017.01.012.
• 10. H Q Li, R Yuan, J Fu. A Reliability Modeling for Multi-Component Systems Considering Random Shocks and Multi-State Degradation[J]. IEEE Access,2019,7. https://doi.org/10.1109/ACCESS.2019.2953483.
• 11. B L Liu, Z Q Zhang, Y Q Wen, et al. Reliability analysis for complex systems subject to competing failure processes in an uncertain environment[J]. Journal of Intelligent & Fuzzy Systems,2020,39(3). https://doi.org/10.3233/JIFS-200343.
• 12. X Y Li, H Z Huang, Y F Li, et al. A Markov regenerative process model for phased mission systems under internal degradation and external shocks[J]. Reliability Engineering and System Safety,2021,215. https://doi.org/10.1016/j.ress.2021.107796.
• 13. H Y Shi, C Wei, Z Q Zhang, et al. Reliability analysis of dependent competitive failure model with uncertain parameters[J]. Soft Computing,2021,26(1). https://doi.org/10.1007/s00500-021-06398-6.
• 14. L Zhang, J G Zhang. Uncertain process–based reliability and maintenance modeling for systems under mutually dependent degradation and shock processes[J]. Quality and Reliability Engineering International,2021,37(08). https://doi.org/10.1002/qre.2938.
• 15. H Lyu, S Wang, X W Zhang, et al. Reliability modeling for dependent competing failure processes with phase-type distribution considering changing degradation rate[J]. Eksploatacja i Niezawodność –Maintenance and Reliability,2021,23(04):627-635. https://doi.org/10.17531/ein.2021.4.5.
• 16. W J Dong, S F Liu, Y S Cao, et al. Time‐based replacement policies for a fault tolerant system subject to degradation and two types of shocks[J]. Quality and Reliability Engineering International,2020,36(07):2338-2350. https://doi.org/10.1002/qre.2700.
• 17. X J Zhou, L F Xi, J Lee. Opportunistic preventive maintenance scheduling for a multi-unit series system based on dynamic programming[J]. International Journal of Production Economics,2009,118(02):361-366. https://doi.org/10.1016/j.ijpe.2008.09.012.
• 18. J.E. Ruiz-Castro. Preventive Maintenance of a Multi-State Device Subject to Internal Failure and Damage Due to External Shocks[J]. IEEE Transactions on Reliability,2014,63(02). https://doi.org/10.1109/TR.2014.2315922.
• 19. N.M. Modak, S. Panda, S.S. Sana. Optimal just-in-time buffer inventory for preventive maintenance with imperfect quality items[J]. TÉKHNE,2015,13(02):135-144. https://doi.org/10.1016/j.tekhne.2016.02.002.
• 20. B H Zhou, Y Qi, Y W Liu. Proactive preventive maintenance policy for buffered serial production systems based on energy saving opportunistic windows[J]. Journal of Cleaner Production,2020,253. https://doi.org/10.1016/j.jclepro.2019.119791.
• 21. L Bi, F Tao, P Y Zhang, et al. Opportunistic maintenance for multi-unit series systems based on gated recurrent units prediction model[J]. CIRP Annals -Manufacturing Technology,2020,69(01). https://doi.org/10.1016/j.cirp.2020.04.019.
• 22. N C Wang, J W Hu, L Ma, et al. Availability Analysis and Preventive Maintenance Planning for Systems with General Time Distributions[J]. Reliability Engineering & System Safety, 2020,201. https://doi.org/10.1016/j.ress.2020.106993.
• 23. Y Chen, Q G Qiu, X Zhao. Condition-based opportunistic maintenance policies with two-phase inspections for continuous-state systems[J]. Reliability Engineering & System Safety,2022,228. https://doi.org/10.1016/j.ress.2022.108767.
• 24. W K Gao, Y Wang, X W Zhang, et al. Quasi-periodic Inspection and Preventive Maintenance Policy Optimisation for a system with Wiener Process degradation[J]. Eksploatacja i Niezawodność –Maintenance and Reliability,2023,25(2):162433. https://doi.org/10.17531/ein/162433.
• 25. Y M Chen, Y Liu, T Jiang. Optimal Maintenance Strategy for Multi-State Systems with Single Maintenance Capacity and Arbitrarily Distributed Maintenance Time[J]. Reliability Engineering & System Safety,2021,211. https://doi.org/10.1016/j.ress.2021.107576.
• 26. Q N Liu, L Ma, N C Wang, et al. A condition-based maintenance model considering multiple maintenance effects on the dependent failure processes[J]. Reliability Engineering & System Safety,2022,220. https://doi.org/10.1016/j.ress.2021.108267.
• 27. L R Cui, Z L Chen, H D Gao. Reliability for systems with self-healing effect under shock models[J]. Nephron Clinical Practice.2018,15(5):551-567. https://doi.org/10.1080/16843703.2016.1264146.
• 28. X Zhao, X X Guo, X Y Wang. Reliability and maintenance policies for a two-stage shock model with self-healing mechanism[J]. Reliability Engineering and System Safety,2018,172. https://doi.org/10.1016/j.ress.2017.12.013.
• 29. Q G Qiu, L R Cui, B Wu. Dynamic mission abort policy for systems operating in a controllable environment with self-healing mechanism[J]. Reliability Engineering and System Safety,2020,203. https://doi.org/10.1016/j.ress.2020.107069.
• 30. J Y Shen, S S Cong, N Zhang, et al. Reliability modelling and self-healing policy design for systems with limited resources[J]. Reliability Engineering & System Safety,2023,240. https://doi.org/10.1016/j.ress.2023.109537.
• 31. B H Zhou, Y W Liu. Optimal production cycle model considering equipment degradation and stochastic demand[J]. Journal of Harbin Engineering University,2017,38(06):950-955. https://doi.org/10.11990/jheu.201603079.
• 32. M Giorgio, M Guida, F Postiglione, et al. Bayesian estimation and prediction for the transformed gamma degradation process[J]. Quality and Reliability Engineering International,2018,34(07):1315-1328. https://doi.org/10.1002/qre.2329.
• 33. KRafiee, Q M Feng, D W Coit. Reliability Analysis and Condition-based Maintenance for Failure Processes with Degradation-dependent Hard Failure Threshold[J]. Quality and Reliability Engineering International,2017,33(07):1351-1366. https://doi.org/10.1002/qre.2109.