Sequential Preventive Maintenance Strategy Considering Difference of Maintenance Effect

被引:0
|
作者
Li X. [1 ]
Ran Y. [1 ]
Zhang G. [1 ,2 ,3 ]
He Y. [1 ,2 ]
机构
[1] College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing
[2] State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing
[3] School of Intelligent Manufacturing Engineering, Chongqing University of Arts and Sciences, Chongqing
关键词
generalized geometric process(GGP); imperfect maintenance; meta-action unit; preventive maintenance; sequential maintenance;
D O I
10.16183/j.cnki.jsjtu.2022.023
中图分类号
学科分类号
摘要
Proper preventive maintenance can improve equipment reliability and prolong equipment life to a certain extent. Aimed at the problems that the decision granularity of the current preventive maintenance strategy is too large and the maintenance effect of preventive maintenance on different types of failures is rarely considered, the imperfect sequential preventive maintenance strategy of the meta-action unit is studied. Taking the meta-action unit as the research carrier, the failures are divided into damage failure and essential fatigue failure according to the difference of preventive maintenance effect. Based on the generalized geometric process, a sequential preventive maintenance optimization model is established. The research shows that the overall maintenance cost rate will be underestimated without considering the differences in preventive maintenance effectiveness. At the same time, various types of maintenance costs, the proportion factor of damage-type failures and intrinsic fatigue-type failures, and the preventive maintenance effect parameter have a significant influence on the formulation of maintenance strategy. This research has a certain guiding role in formulating the sequential preventive maintenance strategy of meta-action unit and reducing its maintenance cost. © 2023 Shanghai Jiao Tong University. All rights reserved.
引用
收藏
页码:1522 / 1530
页数:8
相关论文
共 18 条
  • [1] DU Yu, LI Yuqing, ZHANG Xiufang, Et al., Preventive maintenance and replacement policy for series deteriorating production system considering generalized time value, Journal of Shanghai Jiao Tong University, 54, 5, pp. 465-472, (2020)
  • [2] HAO Hongfei, GUO Wei, GUI Lin, Et al., A multiobjective preventive maintenance decision-making model for imperfect repair process, Journal of Shanghai Jiao Tong University, 52, 5, pp. 518-524, (2018)
  • [3] WANG H Z., A survey of maintenance policies of deteriorating systems, European Journal of Operational Research, 139, 3, pp. 469-489, (2002)
  • [4] NAKAGAWA T., Periodic and sequential preventive maintenance policies, Journal of Applied Probability, 23, 2, pp. 536-542, (1986)
  • [5] ZHU X Y, BEI X Q, CHATWATTANASIRI N, Et al., Optimal system design and sequential preventive maintenance under uncertain aperiodic-changing stresses, IEEE Transactions on Reliability, 67, 3, pp. 907-919, (2018)
  • [6] ZHOU Y, KOU G, XIAO H, Et al., Sequential imperfect preventive maintenance model with failure intensity reduction with an application to urban buses, Reliability Engineering & System Safety, 198, (2020)
  • [7] DUAN C Q, DENG C, WANG B R., Multi-phase sequential preventive maintenance scheduling for deteriorating repairable systems, Journal of Intelligent Manufacturing, 30, 4, pp. 1779-1793, (2019)
  • [8] SU Chun, HU Zhaoyong, ZHENG Yuqiao, Single part sequential maintenance optimization for wind turbines based on availability constraint, Journal of Southeast University (Natural Science Edition), 49, 1, pp. 110-115, (2019)
  • [9] SUN Q Z, YE Z S, PENG W W., Scheduling preventive maintenance considering the saturation effect, IEEE Transactions on Reliability, 68, 2, pp. 741-752, (2019)
  • [10] ZHANG Genbao, ZHANG Dingfei, RAN Yan, Et al., Performance reliability analysis of meta-action unit based on gamma process and hybrid copula function, Journal of Hunan University (Natural Sciences), 48, 4, pp. 113-125, (2021)