Multi-Stage Opportunistic Maintenance Decision-Making for Electric Multiple Unit Systems with Bi-Objective Optimization

doi:10.16183/j.cnki.jsjtu.2021.104

Abstract

Abstract:

In order to improve operation efficiency of the electric multiple unit when running reliably, a multi-stage opportunistic maintenance decision strategy with bi-objective optimization is proposed based on the traditional opportunistic maintenance strategy. The window of opportunistic maintenance is equidistantly divided into multiple stages, and components located at different stages are maintained by different efforts. Aimed to solve problem of assigning multiple maintenance tasks of components, an assignment algorithm with two repairpersons is proposed. To further improve the multi-attribute optimization performance of this model, the proposed algorithm is introduced into the multi-attribute decision-making. The numerical example analysis verifies the effectiveness of the multi-stage opportunistic maintenance strategy in optimizing availability and average cost rate. Furthermore, the influence of weight factors on optimization tendency is discussed as well.

Key words: maintenance strategy, opportunistic maintenance, multi-stage windows, bi-objective optimization, system of electric multiple unit

CLC Number:

U279.3

WANG Hong, QI Yankun, HE Yong, YANG Guojun. Multi-Stage Opportunistic Maintenance Decision-Making for Electric Multiple Unit Systems with Bi-Objective Optimization[J]. Journal of Shanghai Jiao Tong University, 2022, 56(9): 1276-1284.

Figures/Tables 12

Fig.1

Fig.2

Fig.3

Fig.4

Tab.1

Factors of components

部件	α_j	β_j	R_j	$c p j$ /元	$c j c r$ /元	e_2,_j/d
1	2.5	100	0.75	1 000	2 200	1.1
2	3.2	108	0.80	1 100	2 400	0.7
3	3.1	150	0.85	600	1 500	0.9
4	3.2	149	0.85	700	1 900	0.6
5	2.3	85	0.75	500	1 200	1.2
6	2.6	100	0.70	400	1 000	0.8

Tab.1

Fig.5

Tab.2

Tab.3

Tab.4

Tab.5

Influence of different weight factors on maintenance strategy

方案	权重因子值	C_le/元	C_sys/元	$∑ i = 1 n 2 t l i$ /d	H	A	维修人员数量选择序列
1	ω₁=1,ω₂=0	19 800	48 373	29.24	144.1	0.920	(1,1,1,1,1,1,1,1,1,1,1)
2	ω₁=0.55,ω₂=0.45	19 800	49 996	26.74	147.8	0.927	(1,1,1,1,1,2,1,1,1,1)
3	ω₁=0.53,ω₂=0.47	23 400	53 366	23.25	156.2	0.936	(1,1,1,1,2,2,1,2,1,1)
4	ω₁=0.52,ω₂=0.48	25 200	55 064	21.59	160.3	0.941	(1,1,1,2,2,2,1,2,1,1)
5	ω₁=0.50,ω₂=0.50	30 600	60 273	18.23	173.8	0.950	(1,2,2,2,2,2,2,2,1,1)
6	ω₁=0.44,ω₂=0.56	34 200	63 767	16.18	182.8	0.956	(2,2,2,2,2,2,2,2,2,1)
7	ω₁=0,ω₂=1	36 000	65 537	15.58	187.6	0.957	(2,2,2,2,2,2,2,2,2,2)

Tab.5

Tab.6

Comparison results of number of maintenance repairperson

序号	维修人员数量	$c 6 l e$ + $c 6 r u n$ /元	$t 6 l$ /d
1	1	230 5	5.05
2	2	385 5	2.55

Tab.6

Fig.6

References 17

[1]	PENG H, ZHU Q S. Approximate evaluation of average downtime under an integrated approach of opportunistic maintenance for multi-component systems[J]. Computers & Industrial Engineering, 2017, 109(7): 335-346. doi: 10.1016/j.cie.2017.04.043 URL
[2]	SI G J, XIA T B, ZHU Y, et al. Triple-level opportunistic maintenance policy for leasehold service network of multi-location production lines[J]. Reliability Engineering & System Safety, 2019, 190(10): 106519.
[3]	ZHOU B H, QI Y, LIU Y W. Proactive preventive maintenance policy for buffered serial production systems based on energy saving opportunistic windows[J]. Journal of Cleaner Production, 2019, 253: 119791.
[4]	BA H T, CHOLETTE M E, BORGHESANI P, et al. Opportunistic maintenance considering non-homogenous opportunity arrivals and stochastic opportunity durations[J]. Reliability Engineering & System Safety, 2017, 160: 151-161. doi: 10.1016/j.ress.2016.12.011 URL
[5]	石冠男, 张晓红, 曾建潮. 考虑非完美维修的多部件系统劣化状态空间划分建模[J]. 计算机集成制造系统, 2018, 24(11): 2759-2769.
	SHI Guannan, ZHANG Xiaohong, ZENG Jianchao. Deterioration state space partition method for multi-unit systems with imperfect maintenance actions[J]. Computer Integrated Manufacturing Systems, 2018, 24(11): 2759-2769.
[6]	ZHOU X J, YU M Q. Semi-dynamic maintenance scheduling for multi-station series systems in multi-specification and small-batch production[J]. Reliabi-lity Engineering & System Safety, 2020, 195: 106753.
[7]	SHI H, ZENG J C. Real-time prediction of remaining useful life and preventive opportunistic maintenance strategy for multi-component systems considering stochastic dependence[J]. Computers & Industrial Engineering, 2016, 93(3): 192-204. doi: 10.1016/j.cie.2015.12.016 URL
[8]	ABDOLLAHZADEH H, ATASHGAR K, ABBASI M. Multi-objective opportunistic maintenance optimization of a wind farm considering limited number of maintenance groups[J]. Renewable Energy, 2016, 88(4): 247-261. doi: 10.1016/j.renene.2015.11.022 URL
[9]	DING F F, TIAN Z G. Opportunistic maintenance for wind farms considering multi-level imperfect maintenance thresholds[J]. Renewable Energy, 2012, 45: 175-182. doi: 10.1016/j.renene.2012.02.030 URL
[10]	昝翔, 陈春良, 张仕新, 等. 考虑时间不确定性的战时装备维修任务调度方法[J]. 机械工程学报, 2018, 54(24): 226-232. doi: 10.3901/JME.2018.24.226
	ZAN Xiang, CHEN Chunliang, ZHANG Shixin, et al. Task scheduling method for wartime equipment maintenance considering time uncertainty[J]. Journal of Mechanical Engineering, 2018, 54(24): 226-232. doi: 10.3901/JME.2018.24.226
[11]	杜煜, 李雨青, 张秀芳, 等. 考虑广义时间价值的串行退化生产系统维护更新策略[J]. 上海交通大学学报, 2020, 54(5): 465-472.
	DU Yu, LI Yuqing, ZHANG Xiufang, et al. Preventive maintenance and replacement policy for series deteriorating production system considering genera-lized time value[J]. Journal of Shanghai Jiao Tong University, 2020, 54(5): 465-472.
[12]	王海朋, 段富海, 马骏. 复杂系统的选择性维修模型和求解算法[J]. 北京航空航天大学学报, 2020, 46(12): 2264-2273.
	WANG Haipeng, DUAN Fuhai, MA Jun. Selective maintenance model and its solving algorithm for complex system[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(12): 2264-2273.
[13]	KHATAB A, DIALLO C, VENKATADRI U, et al. Optimization of the joint selective maintenance and repairperson assignment problem under imperfect maintenance[J]. Computers & Industrial Engineering, 2018, 125: 413-422. doi: 10.1016/j.cie.2018.09.012 URL
[14]	DIALLO C, VENKATADRI U, KHATAB A, et al. Optimal joint selective imperfect maintenance and multiple repairpersons assignment strategy for complex multicomponent systems[J]. International Journal of Production Research, 2019, 57(13): 4098-4117. doi: 10.1080/00207543.2018.1505060 URL
[15]	DUAN C Q, DENG C, WANG B R. Multi-phase sequential preventive maintenance scheduling for deteriorating repairable systems[J]. Journal of Intelligent Manufacturing, 2019, 30(4): 1779-1793. doi: 10.1007/s10845-017-1353-z URL
[16]	王灵芝, 徐宇工, 张家栋. 基于设备有效度和可靠度的预防修经济优化模型[J]. 机械工程学报, 2010, 46(4): 163-168.
	WANG Lingzhi, XU Yugong, ZHANG Jiadong. Preventive maintenance economic optimization model based on equipment availability and reliability[J]. Journal of Mechanical Engineering, 2010, 46(4): 163-168.
[17]	王少敏. 动车组转向架关键零部件的故障规律及维修策略研究[D]. 北京: 北京交通大学, 2016.
	WANG Shaomin. Research on failure regularity and maintenance strategy of key components of EMU bogie[D]. Beijing: Beijing Jiaotong University, 2016.

系统维修时机/d	维修部件序号	部件于机会窗口的阶段数
49	1, 5	3, 0
69	2, 3, 4, 6	0, 4, 4, 0
94	1, 5	0, 1
122	2, 3, 4, 5, 6	4, 0, 0, 3, 4
157	1, 2, 5, 6	0, 2, 0, 2
208	1, 2, 3, 4, 5, 6	3, 0, 0, 0, 0, 0
253	1, 5	0, 1
279	2, 3, 4, 5, 6	0, 4, 4, 4, 0
315	1, 3, 5	0, 4, 0
336	2, 4, 6	4, 0, 4

模型	H
模型	P=2	P=3	P=4	P=5	P=6
平均成本率模型	145.5	144.9	144.1	148.8	151.6
综合模型	191.8	189.9	173.8	181.9	175.2
可用度模型	204.8	194.4	187.6	190.7	193.4

模型	A
模型	P=2	P=3	P=4	P=5	P=6
平均成本率模型	0.922	0.919	0.920	0.917	0.914
综合模型	0.945	0.952	0.950	0.950	0.944
可用度模型	0.954	0.955	0.957	0.956	0.954