Optimization Model of Maintenance and Spare Parts Ordering Policy in Multivariate Degradation System

doi:10.16183/j.cnki.jsjtu.2019.221

Abstract

Abstract:

Aimed at the decision-making problem of condition-based maintenance and spare parts ordering for systems with multiple dependent degradation processes, an optimization model of system maintenance and spare parts ordering policy is developed under the condition of continuously monitoring. First, the Gamma process and Copula function are used to develop the system multivariate degradation model. Then, the system maintenance and spare parts ordering policy based on the control limit strategy is proposed. Considering the influence of system degradation on maintenance cost, the analytical expression of the expected maintenance cost rate under long-term operation conditions is obtained. At the same time, an approximate expression of the expected maintenance cost rate is proposed to simplify the model calculation. The optimal preventive replacement threshold and spare parts ordering threshold of the system are obtained by using the artificial bee colony algorithm under the cost criterion. The case analysis shows that it is necessary to consider degradation in maintenance decision-making. Compared with the existing policy, the comprehensive optimization of preventive replacement and spare parts ordering thresholds can effectively reduce the maintenance cost of the system.

Key words: maintenance decision, spare parts ordering, multivariate degradation process, dependent degradation, condition monitoring

CLC Number:

TB114

YANG Zhiyuan, ZHAO Jianmin, CHENG Zhonghua, GUO Chiming, LI Liying. Optimization Model of Maintenance and Spare Parts Ordering Policy in Multivariate Degradation System[J]. Journal of Shanghai Jiao Tong University, 2021, 55(7): 858-867.

Figures/Tables 12

Fig.1

Fig.2

Tab.1

Parameters of system degradation processes and failure thresholds

退化过程	案例1			案例2
退化过程	α_i	β_i	$Q L i$	α_i	β_i	$Q L i$
i=1	1	2	10	1	2	10
i=2	1	2	10	9/4	2/3	8

Tab.1

Tab.2

Tab.3

Comparison of analytical results and MC simulations

案例	( $Q A 1$ , $Q A 2$ , $Q M 1$ , $Q M 2$ )	解析结果	MC仿真结果	MC仿真95% 置信区间
1	(2,2,5,3)	11.25	11.18	[10.75,11.62]
	(4,3,6,5)	10.07	10.02	[9.64,10.40]
	(3,3,8,8)	10.34	10.27	[9.76,10.77]
2	(2,2,3,3)	10.66	10.61	[9.88,11.34]
	(3,2.5,5,5)	9.69	9.67	[9.13,10.21]
	(3,3,7,6)	9.58	9.52	[9.04,10.01]

Tab.3

Fig.3

Fig.4

Fig.5

Tab.4

Fig.6

Fig.7

Tab.5

Optimal system maintenance and spare parts ordering policies at different θ values

θ	案例1					案例2
θ	$Q A 1 *$	$Q A 2 *$	$Q M 1 *$	$Q M 2 *$	$γ ∞ *$	$Q A 1 *$	$Q A 2 *$	$Q M 1 *$	$Q M 2 *$	$γ ∞ *$
0	5.96	5.96	8.53	8.53	9.103	7.18	5.20	8.31	6.83	9.006
0.5	6.07	6.07	8.19	8.19	8.996	6.07	5.44	8.07	6.59	8.763
0.7	5.92	5.92	8.03	8.03	8.922	6.07	5.35	7.96	6.50	8.649
0.9	5.14	5.14	7.82	7.82	8.643	6.27	4.91	7.84	6.39	8.491

Tab.5

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参数	取值
C_I	1
C_O	3
C_S	5
C_LO	50
C_R	10
ρ	20

维修策略	案例1					案例2
维修策略	$Q_{{A}_{1}}^{*}$	$Q_{{A}_{2}}^{*}$	$Q_{{M}_{1}}^{*}$	$Q_{{M}_{2}}^{*}$	$γ_{∞}^{*}$	$Q_{{A}_{1}}^{*}$	$Q_{{A}_{2}}^{*}$	$Q_{{M}_{1}}^{*}$	$Q_{{M}_{2}}^{*}$	$γ_{∞}^{*}$
本文	5.92	5.92	8.03	8.03	8.922	6.07	5.35	7.96	6.50	8.649
文献[14]	—	—	6.06	6.06	9.586	—	—	6.94	4.80	9.192