Search for Author, Title, Keyword
Preventive maintenance of multiple components for hydraulic tension systems
More details
Hide details
School of Management Engineering, Zhengzhou University, Zhengzhou 450001, China
Laboratory of Science and Technology on Integrated Logistics Support, College of Intelligent Sciences and Technology, National University of Defense Technology, Changsha 410073, PR China
Publication date: 2021-09-30
Eksploatacja i Niezawodność – Maintenance and Reliability 2021;23(3):489–497
  • Hydraulic tension system of conveyor belt is introduced to SPM.
  • Preventive maintenance model for multiple components is proposed.
  • Joint integrated importance measure (JIIM) is applied to a hydraulic tension system.
  • Maintenance plan of hydraulic tension is analysed to optimize the system performance.
Automatically controlled hydraulic tension systems adjust the tension force of a conveyor belt under different working conditions. Failures of an automatically controlled hydraulic tension system influence the performance of conveyor belts. At present, the maintenance of automatically controlled hydraulic tension systems mainly considers the replacement of components when failures occur. Considering the maintenance cost and downtime, it is impossible to repair all the failed components to improve the hydraulic tension system. One of the key problems is selecting the most valuable components for preventive maintenance. In this paper, preventive maintenance for multiple components in a hydraulic tension system is analyzed. An index is proposed to select more reliable preventive maintenance components to replace the original ones. A case study is given to demonstrate the proposed method. When the cost budget increases, there are three different variations in the number of components for selective preventive maintenance (SPM).
Cai B P, Huang L, Xie M. Bayesian networks in fault diagnosis. IEEE Transactions on Industrial Informatics 2017; 13(5): 2227-2240, https:/
Cai B P, Yu L, Xie M. A dynamic-bayesian-network-based fault diagnosis methodology considering transient and intermittent faults. IEEE Transactions on Automation Science and Engineering, 2017; 14(1): 276-285, https:/
Cai B P, Shao X Y, Liu Y H, Kong X D, Wang H F, Xu H Q, Ge W F. Remaining useful life estimation of structure systems under the influence of multiple causes: subsea pipelines as a case study. IEEE Transactions on Industrial Electronics, 2020; 67(7): 5737-5747,
Cui J G, Ren Y, Xu B H, Yang D Z, Zeng S K. Reliability analysis of a multi-eso based control strategy for level adjustment control system of quadruped robot under disturbances and failures. Eksploatacja i Niezawodnosc - Maintenance and Reliability, 2020; 22(1): 42-51,
Dui H Y, Li S M, Xing L D, Liu H L. System performance-based joint importance analysis guided maintenance for repairable systems. Reliability Engineering & System Safety, 2019; 186: 162-175,
Dui H Y, Si S B, Yam RCM. Importance measures for optimal structure in linear consecutive-k-out-of-n systems. Reliability Engineering & System Safety, 2018; 169: 339-350,
Dui H Y, Wu S M, Zhao J B. Some extensions of the component maintenance priority. Reliability Engineering and System Safety, 2021; 214:107729.https:/
Dui H Y, Zheng X Q, Wu. S M. Resilience analysis of maritime transportation systems based on importance measures. Reliability Engineering and System Safety, 2021; 209: 107461.
Fan D M, Zhang A B, Feng Q, Cai B P, Liu Y L, Ren Y. Group maintenance optimization of subsea Xmas trees with stochastic dependency. Reliability Engineering & System Safety, 2021; 209: 107450,
Gao X L, Cui L R, Li J. L Analysis for joint importance of components in a coherent system. European Journal of Operational Research, 2007; 182(1): 282-299,
Jiang T, Liu Y. Selective maintenance strategy for systems executing multiple consecutive missions with uncertainty. Reliability Engineering & System Safety, 2020; 193: 106632,
Jia X J, Cui L R. Optimization of joint maintenance strategy for safety-critical systems with different reliability degrees. Expert Systems, 2011; 28(3): 199-208,
Jia X J, Xing L D, Song X Y. Aggregated Markov-based reliability analysis of multi-state systems under combined dynamic environments. Quality and Reliability Engineering International, 2020; 36(3): 846-860,
Jia X J, Xing L D, Li G. Copula-based reliability and safety analysis of safety‐critical systems with dependent failures. Quality and Reliability Engineering International, 2018; 34(5): 928-938,
Kou G, Xiao H, Cao M H, Lee L H. Optimal Computing Budget Allocation for the Vector Evaluated Genetic Algorithm in Multi-objective Simulation Optimization. Automatica, 2021; 129: 109599.
Kozłowski E, Kowalska B, Kowalski D, Mazurkiewicz D. Survival Function in the Analysis of the Factors Influencing the Reliability of Water Wells Operation. Water Resources Management, 2019; 33: 4909–4921.
Kozłowski E, Mazurkiewcz D, Kowalska B, Kowalski D. Application of multidimensional scaling method to identify the factors influencing on reliability of deep wells. In: Burduk A., Chlebus E., Nowakowski T., Tubis A. (eds) Intelligent Systems in Production Engineering and Maintenance. Advances in Intelligent Systems and Computing, 2018; 835: 56-65,
Lee T, Shin S, Cha S, Choi S. Fine position control of a vehicle maintenance lift system using a hydraulic unit activated by magnetorheological valves. Journal of intelligent material systems and structures, 2019; 30(6): 896-907,
Liu D, Wang S P, Tomovic M. Degradation modeling method for rotary lip seal based on failure mechanism analysis and stochastic process. Eksploatacja i Niezawodnosc - Maintenance and Reliability, 2020; 22(3): 381-390,
Mohammad J, Mohammad A, Reza K, Seyed H. Reliability-based maintenance scheduling of hydraulic system of rotary drilling machines. International Journal of Mining Science and Technology, 2013; 23(5): 771-775,
Mohammad R P, Sadigh R, Ashkan H. A simulation approach on reliability assessment of complex system subject to stochastic degradation and random shock. Eksploatacja i Niezawodnosc - Maintenance and Reliability, 2020; 22(2): 370-379,
Si S B, Liu M L, Jiang Z Y, Jin T D, Cai Z Q. System reliability allocation and optimization based on generalized birnbaum importance measure. IEEE Transactions on Reliability, 2019; 68(3): 831-843,
Si S B, Zhao J B, Cai Z Q, Dui H Y. Recent advances in system reliability optimization driven by importance measures. Frontiers of Engineering Management, 2020; 7(3): 335-358,
Sun B, Li Y, Wang Z L, Li Z F, Xia Q, Ren Y, Feng Q, Yang D Z, Qian C. Physics-of-failure and computer-aided simulation fusion approach with a software system for electronics reliability analysis. Eksploatacja i Niezawodnosc - Maintenance and Reliability, 2020; 22(2): 340-351,
Teng R M, Liang J F, Wu G L, Wang D L, Wang X. An optimal preventive maintenance strategy for the hydraulic system of platform firefighting vehicle based on the improved NSGA-II algorithm. Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability, 2018; 233: 978-989,
Wang T, Liu Y J. Dynamic response of platform-riser coupling system with hydro-pneumatic tensioner. Ocean Engineering, 2018; 166(15): 172-181,
Wu S M, Castrob I T. Maintenance policy for a system with a weighted linear combination of degradation processes. European Journal of Operational Research, 2020; 280(1): 124-133,
Wu S M, Chen Y, Wu Q T, Wang Z L. Linking component importance to optimization of preventive maintenance policy. Reliability Engineering & System Safety, 2016; 146: 26-32,
Wu S M, Coolen F, Liu B. Optimization of maintenance policy under parameter uncertainty using portfolio theory. IISE Transactions, 2016; 49(7): 711-721,
Wu L, Zhou Q. Adaptive sequential predictive maintenance policy with nonperiodic inspection for hard failures. Quality and Reliability Engineering International, 2021, 37(3), 1173-1185.
Xiao H, Chen H, Lee L H. An efficient simulation procedure for ranking the top simulated designs in the presence of stochastic constraints. Automatica, 2019; 103: 106-115,
Xiao H, Gao S, Lee L H. Simulation budget allocation for simultaneously selecting the best and worst subsets. Automatica, 2017; 84: 177-127,
Xiao H, Gao S Y. Simulation budget allocation for selecting the top-m designs with input uncertainty. IEEE Transactions on Automatic Control, 2018; 63(9): 3127-3134,
Xiao H, Lee L H, Morrice D J, Chen C H, Hu X. Ranking and selection for terminating simulation under sequential sampling. IISE Transactions, 2021; 53(7): 735-750.
Yan S F, Ma B, Wang X, Chen J H, Zheng C S. Maintenance policy for oil-lubricated systems with oil analysis data. Eksploatacja i Niezawodnosc - Maintenance and Reliability, 2020; 22(3): 455-464,
Zhao X, Chen M, Nakagawa T. Replacement policies for a parallel system with shortage and excess costs. Reliability Engineering & System Safety, 2016; 150: 89-95,
Zhao X, Lv Z, He, Z, Wang W. Reliability and opportunistic maintenance for a series system with multi-stage accelerated damage in shock environments. Computers & Industrial Engineering, 2019; 137, 106029,
Zhang C, Zhang Y. Common cause and load-sharing failures-based reliability analysis for parallel systems. Eksploatacja i Niezawodnosc - Maintenance and Reliability, 2020; 22(1): 26-34.
Zhu P, Guo Y, Si S, Han J. A stochastic analysis of competing failures with propagation effects in functional dependency gates. IISE Transactions, 2017; 49(11), 1050-1064,
Selective maintenance optimization with stochastic break duration based on reinforcement learning
Yilai Liu, Xinbo Qian
Eksploatacja i Niezawodnosc - Maintenance and Reliability
Mission reliability–centered maintenance approach based on quality stochastic flow network for multistate manufacturing systems
Xiuzhen Yang, Yihai He, Di Zhou, Xin Zheng
Eksploatacja i Niezawodnosc - Maintenance and Reliability