RESEARCH PAPER
Optimal maintenance strategy for imperfect manufacturing system considering operational availability under delay propagation
1
School of Mechanical and Aerospace Engineering, Jilin University, China
2
CHONGQING QINGPING MACHINERY CO.,LTD, China
3
Chongqing Research Institute, Jilin University, China
4
Faw Jiefang Automotive Co.,Ltd, China
Submission date: 2025-03-20
Final revision date: 2025-05-05
Acceptance date: 2025-06-14
Online publication date: 2025-06-14
Publication date: 2025-06-14
Corresponding author
Eksploatacja i Niezawodność – Maintenance and Reliability 2026;28(1):207148
HIGHLIGHTS
- Maintenance strategy integrates operational availability under delay propagation.
- Introducing delay time as a state variable to handle operational availability impacts.
- A Markov Decision Process–Based Condition-Based Maintenance Model.
- A scenario-based value iteration method to solve discrete health states effectively.
KEYWORDS
ReliabilityCondition-based maintenanceImperfect manufacturing systemOperational availabilityDelay propagationMarkov decision process
TOPICS
ABSTRACT
Manufacturing system degradation can damage its reliability, resulting in decreased product quality and delayed deliveries. These challenges are characteristic of imperfect manufacturing systems. Moreover, the propagation of delay time across task periods may reduce the operational availability in future periods. Condition-based maintenance is an effective method for mitigating system degradation and enhancing reliability. However, existing condition-based maintenance studies often overlook the impact of delay propagation on operational availability. To address this issue, this paper proposes a condition-based maintenance model based on a Markov decision process. By introducing delay time as a state variable to capture changes in operational availability and incorporating it into the reward model, the proposed strategy aims to maximize enterprise profit. A case study and comparative analysis using data from a manufacturing enterprise validate the effectiveness and superiority of the proposed model in improving economic performance.
REFERENCES (48)
1.
Rausand M, Høyland A. System Reliability Theory: Models, Statistical Methods, and Applications2003.
2.
Rivera-Gomez H, Gharbi A, Kenne JP, Montano-Arango O, Hernandez-Gress ES. Subcontracting strategies with production and maintenance policies for a manufacturing system subject to progressive deterioration. Int J Prod Econ. 2018;200:103-18. https://doi.org/10.1016/j.ijpe....
3.
Taleizadeh AA, Sari-Khanbaglo MP, Cárdenas-Barrón LE. Outsourcing Rework of Imperfect Items in the Economic Production Quantity (EPQ) Inventory Model With Backordered Demand. IEEE Trans Syst Man Cybern -Syst. 2019;49:2688-99. https://doi.org/10.1109/TSMC.2....
4.
Lai XF, Chen ZX, Bidanda B. Optimal decision of an economic production quantity model for imperfect manufacturing under hybrid maintenance policy with shortages and partial backlogging. Int J Prod Res. 2019;57:6061-85. https://doi.org/10.1080/002075....
5.
Zhang C, Zhang YD, Dui H, Wang SP, Tomovic MM. Component Maintenance Strategies and Risk Analysis for Random Shock Effects Considering Maintenance Costs. Eksploat Niezawodn. 2023;25:12. https://doi.org/10.17531/ein/1....
6.
Yang XZ, He YH, Liao RY, Cai YQ, Dai W. Mission reliability-centered opportunistic maintenance approach for multistate manufacturing systems. Reliab Eng Syst Saf. 2024;241:15. https://doi.org/10.1016/j.ress....
7.
Li H, Huang C-G, Guedes Soares C. A real-time inspection and opportunistic maintenance strategies for floating offshore wind turbines. Ocean Engineering. 2022;256. https://doi.org/10.1016/j.ocea....
8.
Li H, Teixeira AP, Guedes Soares C. A two-stage Failure Mode and Effect Analysis of offshore wind turbines. Renewable Energy. 2020;162:1438-61. https://doi.org/10.1016/j.rene....
9.
Zhao HS, Xu FH, Liang BT, Zhang JP, Song P. A condition-based opportunistic maintenance strategy for multi-component system. Struct Health Monit. 2019;18:270-83. https://doi.org/10.1177/147592....
10.
Tsao YC, Pantisoontorn A, Vu TL, Chen TH. Optimal production and predictive maintenance decisions for deteriorated products under advance-cash-credit payments. Int J Prod Econ. 2024;269:12. https://doi.org/10.1016/j.ijpe....
11.
Song MQ, Zhang YZ, Yang F, Wang XF, Guo GM. Maintenance policy of degradation components based on the two-phase Wiener process. Eksploat Niezawodn. 2023;25:12. https://doi.org/10.17531/ein/1....
12.
Xu WG, Cao L. Optimal maintenance control of machine tools for energy efficient manufacturing. Int J Adv Manuf Technol. 2019;104:3303-11. https://doi.org/10.1007/s00170....
13.
Xu J, Liang ZL, Li YF, Wang KB. Generalized condition-based maintenance optimization for multi-component systems considering stochastic dependency and imperfect maintenance. Reliab Eng Syst Saf. 2021;211:20. https://doi.org/10.1016/j.ress....
14.
Zhang Q, Liu Y, Xiang Y, Xiahou T. Reinforcement learning in reliability and maintenance optimization: A tutorial. Reliab Eng Syst Saf. 2024;251. https://doi.org/10.1016/j.ress....
15.
Zhang JL, Lam WHK, Chen BY. On-time delivery probabilistic models for the vehicle routing problem with stochastic demands and time windows. Eur J Oper Res. 2016;249:144-54. https://doi.org/10.1016/j.ejor....
16.
Li S, Yang Z, He J, Li G, Yang H, Liu T, et al. A novel maintenance strategy for manufacturing system considering working schedule and imperfect maintenance. Comput Ind Eng. 2023;185. https://doi.org/10.1016/j.cie.....
17.
Shi LX, Lv XL, He YD, He Z. Optimising production, maintenance, and quality control for imperfect manufacturing systems considering timely replenishment. Int J Prod Res. 2024;62:3504-25. https://doi.org/10.1080/002075....
18.
Ait-El-Cadi A, Gharbi A, Dhouib K, Artiba A. Integrated production, maintenance and quality control policy for unreliable manufacturing systems under dynamic inspection. Int J Prod Econ. 2021;236:20. https://doi.org/10.1016/j.ijpe....
19.
Zhang QL, Yang L, Duan JG, Qin JY, Zhou Y. Research on integrated scheduling of equipment predictive maintenance and production decision based on physical modeling approach. Eksploat Niezawodn. 2024;26:15. https://doi.org/10.17531/ein/1....
20.
Guendouli E, Mifdal L, Dellagi S, Kibbou E, Moufki A. Integrated production-maintenance strategy considering energy consumption and recycling constraints in dry machining. Int J Adv Manuf Technol. 2024:19. https://doi.org/10.21203/rs.3.....
21.
Yin ML, Angus JE, Trivedi KS. Optimal Preventive Maintenance Rate for Best Availability With Hypo-Exponential Failure Distribution. Ieee Transactions on Reliability. 2013;62:351-61. https://doi.org/10.1109/TR.201....
22.
Chalabi N, Dahane M, Beldjilali B, Neki A. Optimisation of preventive maintenance grouping strategy for multi-component series systems: Particle swarm based approach. Comput Ind Eng. 2016;102:440-51. https://doi.org/10.1016/j.cie.....
23.
Lotovskyi E, Teixeira AP, Soares CG. Availability analysis of an offshore oil and gas production system subjected to age-based preventive maintenance by Petri Nets. Eksploat Niezawodn. 2020;22:627-37. https://doi.org/10.17531/ein.2....
24.
Yang M, Li CB, Tang Y, Xiong MK. Availability-Oriented Maintenance Strategy of Key Equipment in Automated Production Line Considering Performance Degradation. IEEE Robot Autom Lett. 2023;8:3182-9. https://doi.org/10.1109/LRA.20....
25.
An D, Lee DJ. Optimal condition-based maintenance policy considering nested conditional value-at-risk and operational availability: A case study on semiconductor manufacturing equipment. IISE Trans. 2024:12. https://doi.org/10.1080/247258....
26.
Chen Y, Liu Y, Xiahou T. A Deep Reinforcement Learning Approach to Dynamic Loading Strategy of Repairable Multistate Systems. IEEE Transactions on Reliability. 2022;71:484-99. https://doi.org/10.1109/TR.202....
27.
Wang J, Zhu XY. Joint optimization of condition-based maintenance and inventory control for a k-out-of-n:F system of multi-state degrading components. Eur J Oper Res. 2021;290:514-29. https://doi.org/10.1016/j.ejor....
28.
Hu JW, Sun QZ, Ye ZS. Replacement and Repair Optimization for Production Systems Under Random Production Waits. Ieee Transactions on Reliability. 2022;71:1488-500. https://doi.org/10.1109/TR.202....
29.
Zhang ZS, Zhou YF, Sun Y, Ma L. Condition-Based Maintenance Optimisation Without A Predetermined Strategy Structure For A Two-Component Series System. Eksploat Niezawodn. 2012;14:120-9.
30.
Zhou YF, Zhang ZS. Optimal Maintenance Of A Series Production System With Two Multi-Component Subsystems And An Intermediate Buffer. Eksploat Niezawodn. 2015;17:314-25. https://doi.org/10.17531/ein.2....
31.
Tang DY, Sheng WB, Yu JS. Dynamic Condition-Based Maintenance Policy For Degrading Systems Described By A Random-Coefficient Autoregressive Model: A Comparative Study. Eksploat Niezawodn. 2018;20:590-601. https://doi.org/10.17531/ein.2....
32.
Liu YL, Qian XB. Selective maintenance optimization with stochastic break duration based on reinforcement learning. Eksploat Niezawodn. 2022;24:771-84. https://doi.org/10.17531/ein.2....
33.
Liao HT, Elsayed EA, Chan LY. Maintenance of continuously monitored degrading systems. Eur J Oper Res. 2006;175:821-35. https://doi.org/10.1016/j.ejor....
34.
Zhao X, Sun JL, Qiu QG, Chen K. Optimal inspection and mission abort policies for systems subject to degradation. Eur J Oper Res. 2021;292:610-21. https://doi.org/10.1016/j.ejor....
35.
Bertsekas D, Tsitsiklis JN. Introduction to probability: Athena Scientific; 2008.
36.
Bouslah B, Gharbi A, Pellerin R. Integrated production, sampling quality control and maintenance of deteriorating production systems with AOQL constraint. Omega-Int J Manage Sci. 2016;61:110-26. https://doi.org/10.1016/j.omeg....
37.
van Noortwijk JM. A survey of the application of gamma processes in maintenance. Reliab Eng Syst Saf. 2009;94:2-21. https://doi.org/10.1016/j.ress....
38.
Applebaum D. Lévy Processes and Stochastic Calculus, Second Edition: Springer; 2009. https://doi.org/10.1017/CBO978....
39.
Özekici S. Markov modulated Bernoulli process. Mathematical Methods of Operations Research. 1997;45:311-24. https://doi.org/10.1007/BF0119....
40.
Maillart LM, Cassady CR, Honeycutt J. A binomial approximation of lot yield under Markov modulated Bernoulli item yield. IIE Trans. 2008;40:459-67. https://doi.org/10.1080/074081....
42.
Bellman RE. Dynamic Programming: Princeton Landmarks in Mathematics and Physics; 2021.08. https://doi.org/10.2307/j.ctv1....
43.
Howard RA. Dynamic programming and Markov processes: Technology Press of Massachusetts Institute of Technology; 1960.
44.
Watkins CJCH, Dayan P. Q-learning. Machine Learning. 1992;8:279-92. https://doi.org/10.1007/BF0099....
45.
Williams RJ. Simple statistical gradient-following algorithms for connectionist reinforcement learning. Machine Learning. 1992;8:229-56. https://doi.org/10.1007/BF0099....
46.
Liu Y, Chen Y, Jiang T. Dynamic selective maintenance optimization for multi-state systems over a finite horizon: A deep reinforcement learning approach. Eur J Oper Res. 2020;283:166-81. https://doi.org/10.1016/j.ejor....
47.
Sun QZ, Ye ZS, Chen N. Optimal Inspection and Replacement Policies for Multi-Unit Systems Subject to Degradation. Ieee Transactions on Reliability. 2018;67:401-13. https://doi.org/10.1109/TR.201....
48.
Huang J, Chang Q, Arinez J. Deep reinforcement learning based preventive maintenance policy for serial production lines. Expert Syst Appl. 2020;160:14. https://doi.org/10.1016/j.eswa....
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