基于仿真的多部件系统状态维修决策优化方法

doi:10.3969/j.issn.1000-1093.2017.03.021

兵工学报 ›› 2017, Vol. 38 ›› Issue (3): 568-575.doi: 10.3969/j.issn.1000-1093.2017.03.021

基于仿真的多部件系统状态维修决策优化方法

王少华¹，张耀辉¹，徐隆洋¹，刘宏祥²

(1.装甲兵工程学院技术保障工程系，北京 100072； 2.装甲兵工程学院科研部，北京 100072)

收稿日期:2016-05-13 修回日期:2016-05-13 上线日期:2017-04-24
作者简介:王少华（1986—），男，讲师，博士。E-mail:aafe77330@163.com
基金资助:
军队科研计划项目(51327020303)

Optimal Condition-based Maintenance Decision-making Method of Multi-component System Based on Simulation

WANG Shao-hua¹, ZHANG Yao-hui¹, XU Long-yang¹, LIU Hong-xiang²

(1.Department of Technology Support Engineering, Academy of Armored Force Engineering, Beijing 100072, China; 2.Department of Science Research, Academy of Armored Force Engineering, Beijing 100072, China)

Received:2016-05-13 Revised:2016-05-13 Online:2017-04-24

摘要/Abstract

摘要： 为通过部件组合维修提高维修效益，对采用状态维修的多部件系统，建立了部件状态随机劣化模型。采用幂指数函数建立以状态值为变量的可靠度函数，在考虑不完全维修、维修时间随机分布等因素的条件下，采用蒙特卡洛仿真方法建立了系统状态劣化过程模型。以单位寿命费用最小为优化目标，建立了多部件系统状态维修阈值的优化决策模型。案例分析结果表明，建立的状态维修决策优化模型能够显著降低维修费用、提高系统可用度，是适用且有效的。

关键词: 兵器科学与技术, 状态维修, 不完全维修, 蒙特卡洛仿真, 决策优化

Abstract: To promote the maintenance benefit by combined maintenance, for multi-component systems subjected to condition-based maintenance each component is supposed to endure independent gradual deterioration, and a stochastic deteriorate model is established. The exponential function is applied to set up the reliability functions taking condition parameters as variables. In consideration of imperfect maintenance and probability distribution of maintenance time, a Monte Carlo-based condition deteriorating simulation model of multi-component system is proposed. TA preventive maintenance threshold optimization model is constructed by taking the expected expenses per unit time as the optimization objective, and is verified by a case study. Key

Key words: ordnancescienceandtechnology, condition-basedmaintenance, imperfectmaintenance, MonteCarlosimulation, optimaldecision-making

中图分类号:

王少华，张耀辉，徐隆洋，刘宏祥. 基于仿真的多部件系统状态维修决策优化方法[J]. 兵工学报, 2017, 38(3): 568-575.

WANG Shao-hua, ZHANG Yao-hui, XU Long-yang, LIU Hong-xiang. Optimal Condition-based Maintenance Decision-making Method of Multi-component System Based on Simulation[J]. Acta Armamentarii, 2017, 38(3): 568-575.

参考文献

［1］ Bengtsson M. Condition based maintenance system technology-where is development heading?[C]∥17th European Maintenance Congress. Barcelona, Spain: Euro Maintenance, 2004:580-588.
[2］张小丽, 陈雪峰, 李兵, 等. 机械重大装备寿命预测综述[J].机械工程学报, 2011, 47(11):100-116.
ZHANG Xiao-li, CHEN Xue-feng, LI Bing,et al.Review on life prediction of major mechanized equipment[J]. Journal of Mechanical Engineering, 2011, 47(11):100-116.(in Chinese)
[3］ Wang W. Modeling condition monitoring intervals: a hybrid of simulation and analytical approaches[J]. Journal of the Operational Research Society, 2003, 54(3):273-282.
[4］ Marseguerra M, Zio E. Optimizing maintenance and repair polices via a combination of generic algorithms and Monte Carlo simulation[J]. Reliability Engineering & System Safety, 2000, 68(1): 69-83.
[5］ Bérenguer C, Grall A, Castanier B. Simulation and evaluation of condition-based maintenance polices for multi-component continuous-state deteriorating system[C]∥Foresight and Precaution: Proceedings of ESREL 2000, SARS and SRA-Europe Annual Conference. Amsterdam, Dutch:August Aimé Balkema, 2000:275-282.
[6］ Doostparast M, Kolahan F, Doostparast M. A reliability-based approach to optimize preventive maintenance scheduling for coherent systems[J]. Reliability Engineering & System Safety. 2014, 126: 98-106.
[7］ Hai C V, Do P, Barros A. Maintenance grouping strategy for multi-component systems with dynamic contexts[J]. Reliability Engineering & System Safety, 2014, 132:233-249.
[8］ Zhu W J, Fouladirad M, Bérenguerc C. A multi-level maintenance policy for a multi-component and multifailure mode system with two independent failure modes[J]. Reliability Engineering & System Safety, 2016,153: 50-63.
[9］ Barker C T, Newby M J. Optimal non-periodic inspection for a multivariate degradation model[J]. Reliability Engineering & System Safety, 2009(1):33-43.
[10］ Amari S V, Mclaughlin L. Optimal design of a condition-based maintenance model[C]∥Annual Reliability and Maintainability Symposium. Los Angeles, CA, US:IEEE, 2004:528-533.
[11］ Wang W, Majid H B A. Reliability data analysis and modeling of offshore oil platform plant[J]. Journal of Quality in Maintenance Engineering, 2000, 6(4):287-295.
[12］ Ghasemi A, Yacout S, Ouali M S. Optimal condition based maintenance with imperfect information and the proportional hazard model[J]. International Journal of Production Research, 2007, 45(4): 989-1012.

第38卷
第3期2017 年3月兵工学报ACTA
ARMAMENTARIIVol.38No.3Mar.2017

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基于仿真的多部件系统状态维修决策优化方法

Optimal Condition-based Maintenance Decision-making Method of Multi-component System Based on Simulation

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