Selective Maintenance Decision-Making of Complex Systems Considering Imperfect Maintenance

doi:10.23940/IJPE.18.12.P6.29602970

Abstract

Abstract:

Aiming at enhancing the mission reliability of complex systemscomposed of sequential-parallel parts, a sequential condition deterioration process model was constructed. To better illustrate the effect of varied maintenance behaviors, minimal maintenance, imperfect maintenance, and replacement were taken as optional maintenance actions and modeled. To achieve the maximization of current reliability, a selective maintenance decision-making model and the attached artificial solving measures were brought forward. The case study showed that by integrating the service age reduction model and hazard adjusting model, the imperfect maintenance model can model the actual reliability of the system better. Also, within a given maintenance time, imperfect maintenance was useful for offering more feasible maintenance plans, and the system reliability can be better promoted as a result.

Key words: the mission interval, selective maintenance, imperfect maintenance, genetic algorithm

Shaohua Wang, Shixin Zhang, Yong Li, Hongxiang Liu, and Zhengjun Peng. Selective Maintenance Decision-Making of Complex Systems Considering Imperfect Maintenance [J]. Int J Performability Eng, 2018, 14(12): 2960-2970.

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Figures/Tables 11

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References 14

[1]	Q. Z. Zheng, L. M. Guo, H. P. Shi, N. Wang , “Selective Maintenance Problem for Series-Parallel System under Economic Dependence,” Defence Technology, Vol.12, No. 5, pp. 388-400, 2016 doi: 10.1016/j.dt.2016.04.004
[2]	W.B. Liu, S. H. Wang, X. H. Meng, Wu Chen ,“Equipment Maintenance Task Scheduling based on Genetic Algorithm,” Ordnance Industry Automation, Vol.29,No. 11, pp. 21-26, 2010
[3]	F. M. Liu, H. P. Zhu, B. X. Liu , “Maintenance Decision-Making Method for Manufacturing System based on Cost and Arithmetic Reduction of Intensity Model,” Journal of Central South University, Vol. 20, No. 6, pp. 1559-1571, 2013 doi: 10.1007/s11771-013-1648-y
[4]	Y. Liu, Y. M. Chen, T. Jiang , “On Sequence Planning for Selective Maintenance of Multi-State Systems under Stochastic Maintenance Durations,” European Journal of Operational Research, Vol. 268, No. 1, pp. 113-127, 2018 doi: 10.1016/j.ejor.2017.12.036
[5]	R. E. Wildeman, R. Dekker, A. C. J. M. Smit , “A Dynamic Policy for Grouping Maintenance Activities,” European Journal of Operational Research, Vol.99, No. 3, pp. 530-551, 1997 doi: 10.1016/S0377-2217(97)00319-6
[6]	X. Yao, M. Fu, S. I. Marcus , et al., “Optimization of Preventive Maintenance Scheduling for Semiconductor Manufacturing Systems: Models and Implementation,” in Proceedings of the 2001 IEEE International Conference on Control Applications (CCA’01), pp. 407-411, Mexico City, Mexico, 5-7, September 2001 doi: 10.1109/CCA.2001.973899
[7]	C.R. Cassady, W.P. Murdock, E.A. Pohl , “Selective Maintenance for Support Equipment Involving Multiple Maintenance Actions,” European Journal of Operational Research, Vol.129, No. 2, pp. 252-258, 2001 doi: 10.1016/S0377-2217(00)00222-8
[8]	M. Samrout, F. Yalaoui, E. Chaˆtelet , “New Methods to Minimize the Preventive Maintenance Cost of Series-Parallel Systems Using Ant Colony Optimization,” Reliability Engineering and System Safety, Vol. 89, No. 3, pp. 346-354, 2005 doi: 10.1016/j.ress.2004.09.005
[9]	K.S. Moghaddam and J. S. Usher , “A New Multi-Objective Optimization Model for Preventive Maintenance and Replacement Scheduling of Multi-Component Systems,” Engineering Optimization,Vol.43,No. 7, pp. 701-719,2011 doi: 10.1080/0305215X.2010.512084
[10]	M. Pandey, M. J. Zuo, R. Moghaddass , et al., “Selective Maintenance for Binary Systems under Imperfect Repair,” Reliability Engineering and System Safety, Vol. 113, pp. 42-51, May 2013 doi: 10.1016/j.sess.2012.12.009
[11]	C. Diallo, U. Venkatadri, A. Khatab, and Z. J. Liu , “Optimal Selective Maintenance Decisions for Large Serial k -out-of- n: G Systems under Imperfect Maintenance,” Reliability Engineering and System Safety,Vol. 175, pp. 234-245, July 2018
[12]	M. Pandey, M.J. Zuo, R. Moghaddass , “Selective Maintenance Scheduling over a Finite Planning Horizon,” Journal of Risk and Reliability, Vol. 230,No. 2, pp. 162-177, 2016
[13]	P.E. Labeau and M. C. Segovia , “Effective Age Models for Imperfect Maintenance,” Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, Vol. 225, No. 2, pp. 117-130,2011
[14]	W. B. Cao, X. S. Jia, Q. W. Hu, X. J. Su , “Equipment Battlefield Repair Decision-Making Modelling based on Selective Maintenance,” System Engineering and Electronics, Vol.40, No. 1, pp. 98-105, 2018

Y_s(k)	{0, 1}	0	{0, 1}	{0, 1}	{0, 1}	1	0
l_s(k)	0	1	2	…	p_s-2	p_s-1	p_s
X_s(k+1)	{0, 1}	1	1	1	1	1	1

No.	β_s	α_s	l_s	c_s_,_m(l_s)	T_s_,_k(l_s_,_k)	No	β_s	α_s	l_s	c_s_,_m(l_s)	T_s_,_k(l_s_,_k)
1	1.5	300	1	8	0.40	5	2.5	200	1	10	0.30
			2	20	0.75				2	30	0.55
			3	40	1.25				3	40	0.90
			4	45	1.45				4	45	1.15
			5	45	1.80				5	45	1.60
2	2.4	300	1	6	0.40	6	2.0	375	1	15	0.55
			2	20	0.65				2	25	0.75
			3	35	1.00				3	42	1.20
			4	40	1.45				4	45	1.30
			5	40	1.75				5	45	1.80
3	1.6	250	1	8	0.40	7	1.2	400	1	10	0.60
			2	16	0.75				2	26	0.80
			3	40	1.25				3	45	1.40
			4	45	1.45				4	48	1.60
			5	45	1.75				5	48	1.90
4	2.4	175	1	9	0.50	8	1.4	400	1	8	0.45
			2	25	0.75				2	20	0.70
			3	38	1.25				3	42	1.45
			4	40	1.45				4	48	1.60
			5	40	1.75				5	48	1.80

k	1	2	3	4
B(k)	[100,100,100,100,100,100,100,100]	[105.3,107.1,200,106.1,111.3,102.7,200,200]	[205.3,100,100,100,100,202.7,300,300]	[100,200,200,100,100,100,400,400]
Y_s(k)	[0,1,1,1,0,1,1,1]	[1,1,1,1,1,0,1,0]	[1,1,1,0,1,0,1,0]	-
Y(k)	1	1	1	-
L(k)	[4,4,1,4,4,4,1,1]	[1,5,5,5,5,1,1,1]	[5,1,1,4,4,6,1,1]	-
X_s(k +1)	[1,1,1,1,1,1,1,1]	[1,1,1,1,1,0,1,0]	[1,1,1,1,1,1,1,0]	-
X(k +1)	1	1	1	-
T(k)	5.6	5.5	5.4	-
R(k +1)	0.9365	0.9470	0.9276	-