Sequential Preventive Maintenance Strategy Considering Difference of Maintenance Effect

doi:10.16183/j.cnki.jsjtu.2022.023

Abstract

Abstract:

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.

Key words: preventive maintenance, meta-action unit, generalized geometric process(GGP), sequential maintenance, imperfect maintenance

CLC Number:

TH17

LI Xinlong, RAN Yan, ZHANG Genbao, HE Yan. Sequential Preventive Maintenance Strategy Considering Difference of Maintenance Effect[J]. Journal of Shanghai Jiao Tong University, 2023, 57(11): 1522-1530.

Figures/Tables 9

Fig.1

Fig.2

Fig.3

Tab.1

Influence of minimal maintenance cost c m 1 of damage-type failures on optimal maintenance strategy

$c m 1$ /元	C^*/(元·h^-1)	N^*	维修间隔时间序列,x₁,…,x_k/h	更新周期长度/h
10	4.94	3	562.29, 354.81, 269.32	1 186.42
20	6.33	4	411.04, 268.80, 208.41, 170.22	1 058.46
30	7.54	5	332.41, 221.08, 173.26, 142.59, 118.94	988.28
40	8.64	5	283.04, 190.11, 149.95, 123.98, 103.79	850.87
50	9.67	5	248.68, 168.11, 133.17, 110.46, 92.69	753.10
60	10.65	6	223.14, 151.53, 120.41, 100.1, 84.145, 70.46	749.80
70	11.58	6	203.29, 138.52, 110.33, 91.88, 77.33, 64.82	686.17
80	12.45	6	187.34, 127.98, 102.12, 85.16, 71.75, 60.19	634.53
90	13.33	6	174.18, 119.24, 95.284, 79.54, 67.08, 56.31	591.64
100	14.16	6	163.12, 111.86, 89.49, 74.77, 63.10, 53.00	555.33

Tab.1

Tab.2

Influence of minimal maintenance cost c m 2 on optimal maintenance strategy for intrinsic fatigue-type failures

$c m 2$ /元	C^*/(元·h^-1)	N^*	维修间隔时间序列,x₁,…,x_k/h	更新周期长度/h
10	8.39	6	266.39, 184.66, 148.86, 125.11, 106.07, 89.40	920.48
20	8.65	6	262.60, 181.03, 145.36, 121.80, 103.01, 86.66	900.45
30	8.92	6	258.94, 177.57, 142.05, 118.69, 100.16, 84.12	881.54
40	9.17	6	255.40, 174.27, 138.93, 115.78, 97.51, 81.77	863.65
50	9.43	6	251.98, 171.12, 135.98, 113.04, 95.02, 79.56	846.70
60	9.67	5	248.68, 168.11, 133.17, 110.46, 92.69	753.10
70	9.91	5	245.48, 165.23, 130.51, 108.02, 90.49	739.72
80	10.14	5	242.38, 162.46, 127.97, 105.70, 88.42	726.94
90	10.37	5	239.38, 159.82, 125.56, 103.51, 86.46	714.73
100	10.60	5	236.47, 157.27, 123.25, 101.43, 84.61	703.04

Tab.2

Tab.3

Tab.4

Tab.5

Tab.6

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c_p/元	C^*/(元·h^-1)	N^*	维修间隔时间序列,x₁,…,x_k/h	更新周期长度/h
100	8.76	7	248.68, 158.63, 120.17, 96.17, 78.38, 63.97, 51.80	817.83
200	9.67	5	248.68, 168.11, 133.17, 110.46, 92.69	753.10
300	10.33	4	248.68, 177.32, 145.57, 123.86	695.43
400	10.85	4	248.68, 186.30, 157.46, 136.58	729.02
500	11.25	3	248.68, 195.07, 168.92	612.66
600	11.60	2	248.68, 203.65	452.32
700	11.84	2	248.68, 212.05	460.72
800	12.06	1	248.68	248.68
900	12.06	1	248.68	248.68
1000	12.06	1	248.68	248.68

c_r/元	C^*/(元·h^-1)	N^*	维修间隔时间序列,x₁,…,x_k/h	更新周期长度/h
200	7.05	1	85.05	85.05
300	7.87	2	111.44, 93.781	205.22
400	8.29	3	135.00, 105.90, 91.70	332.60
500	8.61	4	156.66, 117.36, 99.19, 86.04	459.25
600	8.86	4	176.91, 128.29, 106.41, 91.18	502.78
700	9.10	5	196.05, 138.77, 113.39, 96.17, 82.07	626.47
800	9.30	5	214.31, 148.87, 120.17, 101.05, 85.68	670.07
900	9.49	5	231.81, 158.63, 126.75, 105.81, 89.22	712.22
1000	9.67	5	248.68, 168.11, 133.17, 110.46, 92.69	753.10

e	f	C^*/(元·h^-1)	N^*	维修间隔时间序列,x₁,…,x_k/h	更新周期长度/h
0.1	0.9	13.29	1	225.66	225.66
0.2	0.8	13.14	1	228.25	228.25
0.3	0.7	12.99	1	230.91	230.91
0.4	0.6	12.69	2	233.65, 139.68	373.32
0.5	0.5	11.27	2	236.47, 144.39	380.86
0.6	0.4	11.79	3	239.38, 149.52, 112.84	501.73
0.7	0.3	11.20	3	242.38, 155.13, 118.72	516.22
0.8	0.2	10.8	4	245.48, 161.29, 125.43, 102.65	634.85
0.9	0.1	9.67	5	248.68, 168.11, 133.17, 110.46, 92.69	753.10
1.0	0	8.70	7	251.98, 175.69, 142.23, 119.93, 101.94, 86.104, 71.72	949.61

ν	C^*/(元·h^-1)	N^*	维修间隔时间序列,x₁,…,x_k/h	更新周期长度/h
0.02	9.93	4	248.68, 164.87, 125.12, 96.99	635.65
0.04	10.27	4	248.68, 158.5, 110.1, 74.06	591.33
0.06	10.48	3	248.68, 152.27, 96.51	497.46
0.08	10.66	3	248.68, 146.19, 84.29	479.16
0.1	10.83	3	248.68, 140.27, 73.36	462.31
0.3	11.60	2	248.68, 89.64	338.32
0.5	12.06	1	248.68	248.68
0.7	12.06	1	248.68	248.68
0.7	12.06	1	248.68	248.68