Opportunistic Maintenance Modeling for Serial Production Systems with Stochastic Production Waits

doi:10.16183/j.cnki.jsjtu.2020.320

Abstract

Abstract:

In order to make full use of the maintenance opportunities brought by stochastic production waits caused by external factors such as shortage of raw materials and insufficient demands, the notions of mass center and gravity windows are introduced and an opportunity maintenance decision-making model combining the time window and the gravity window is proposed for multi-unit serial production systems. Considering both internal maintenance opportunities caused by equipment mandatory maintenance and external maintenance opportunities caused by production waits, the optimal maintenance strategy is obtained by minimizing the total maintenance cost rate of the system in the planning period. The example analysis shows that the combination of the time window and the gravity window has prominent advantages in reducing the total maintenance cost, and can effectively solve the uncertainty of the arrival and duration of production waits.

Key words: multi-unit serial system, production waits, opportunistic maintenance, maintenance time window, maintenance gravity window

CLC Number:

TP16

NING Xiaohan, ZHOU Xiaojun. Opportunistic Maintenance Modeling for Serial Production Systems with Stochastic Production Waits[J]. Journal of Shanghai Jiao Tong University, 2021, 55(10): 1281-1290.

Figures/Tables 12

Fig.1

Fig.2

Fig.3

Fig.4

Tab.1

Equipment parameters

i	$C i M$ /元	$C i CM$ /元	$c i pen$ /(元·h^-1)	$c i d$ /(元·h^-1)	$τ i M$ /h	α_i	β_i	θ_i
1	513	628.0	52.3	1748	3.42	3.10	67.00	0.97
2	507	711.0	44.8	1802	3.31	2.90	84.24	0.95
3	535	998.0	37.2	2378	3.00	3.03	107.78	0.98
4	629	1131.2	53.4	2752	3.20	2.88	103.36	0.95
5	908	876.0	51.4	1822	2.89	3.12	78.59	0.98
6	545	884.0	37.2	1804	3.14	3.70	98.26	0.97

Tab.1

Tab.2

Fig.5

Fig.6

Tab.3

Simulation results of different downtime costs

κ	$T wi n *$ /h	F^*/kN	c $' 0 sys$ /(元·h^-1)	c $' 1 sys$ /(元·h^-1)	c $' 2 sys$ /(元·h^-1)	ϕ/%
0.10	60	2.9	318.71527	281.8392	274.4371	16.72
0.20	80	4.0	411.60728	361.1766	346.2340	22.86
0.40	90	3.7	506.00181	437.2519	412.4909	26.48
0.50	100	3.9	562.58874	490.8783	462.2401	28.54
0.80	90	4.2	656.73353	586.2013	524.3467	46.72
1.00	80	4.9	727.86663	668.7855	583.4952	59.08
1.25	140	4.5	783.24224	723.1189	624.9857	62.01
2.00	180	4.0	985.13845	913.2768	741.1534	70.55
2.50	210	7.2	1057.89010	989.7344	813.1143	72.16
5.00	240	5.9	1572.10250	1509.0660	1159.1510	84.74
10.00	340	5.4	2433.61210	2400.6480	2192.5110	86.33
25.00	470	6.2	4006.10830	3993.2380	3897.1900	88.18
50.00	560	13.0	6785.66750	6780.4334	6667.2504	95.58

Tab.3

Fig.7

Fig.8

Tab.4

Simulation results of different production wait frequencies

λ/(次·h^-1)	T^win*/h	F^*/kN	c $' 0 sys$ /(元·h^-1)	c $' 1 sys$ /(元·h^-1)	c $' 2 sys$ /(元·h^-1)	ϕ/%
1/40	80	1.6	838.8713	726.1197	656.9259	38.03
1/30	70	1.4	779.4774	689.2100	607.4620	47.52
1/25	60	1.9	755.5036	681.5043	585.6525	56.43
1/20	80	4.9	727.8666	668.7855	583.4952	59.08
1/15	180	5.1	703.8952	642.5038	536.2920	63.37
1/10	220	5.3	646.6898	612.3003	520.2427	72.80
1/5	180	1.0	609.5262	600.1814	482.0396	92.67

Tab.4

References 16

[1]	XIA T B, XI L F, ZHOU X J, et al. Dynamic maintenance decision-making for series-parallel manufacturing system based on MAM-MTW methodology[J]. European Journal of Operational Research, 2012, 221(1):231-240. doi: 10.1016/j.ejor.2012.03.027 URL
[2]	俞梦琦, 史凯龙, 周晓军. 基于双时间窗的多设备串行系统机会维护策略[J]. 上海交通大学学报, 2020, 54(1):69-75.
	YU Mengqi, SHI Kailong, ZHOU Xiaojun. Opportunistic maintenance strategy for multi-unit serial systems based on dual time window[J]. Journal of Shanghai Jiao Tong University, 2020, 54(1):69-75.
[3]	ZHOU P, YIN P T. An opportunistic condition-based maintenance strategy for offshore wind farm based on predictive analytics[J]. Renewable and Sustainable Energy Reviews, 2019, 109:1-9.
[4]	ZHAO H S, XU F H, LIANG B T, et al. A condition-based opportunistic maintenance strategy for multi-component system[J]. Structural Health Monitoring, 2019, 18(1):270-283. doi: 10.1177/1475921717751871 URL
[5]	NGUYEN K A, DO P, GRALL A. Multi-level predictive maintenance for multi-component systems[J]. Reliability Engineering & System Safety, 2015, 144:83-94. doi: 10.1016/j.ress.2015.07.017 URL
[6]	ZHOU X J, XI L F, LEE J. Opportunistic preventive maintenance scheduling for a multi-unit series system based on dynamic programming[J]. International Journal of Production Economics, 2009, 118(2):361-366. doi: 10.1016/j.ijpe.2008.09.012 URL
[7]	DO VAN P, BARROS A, BÉRENGUER C, et al. Dynamic grouping maintenance with time limited opportunities[J]. Reliability Engineering & System Safety, 2013, 120:51-59. doi: 10.1016/j.ress.2013.03.016 URL
[8]	NZUKAM C, VOISIN A, LEVRAT E, et al. Opportunistic maintenance scheduling with stochastic opportunities duration in a predictive maintenance strategy[J]. IFAC-PapersOnLine, 2018, 51(11):453-458.
[9]	KHATAB A, AGHEZZAF E H, DIALLO C, et al. Selective maintenance optimisation for series-parallel systems alternating missions and scheduled breaks with stochastic durations[J]. International Journal of Production Research, 2017, 55(10):3008-3024. doi: 10.1080/00207543.2017.1290295 URL
[10]	LI P, WANG W B, PENG R. Age-based replacement policy with consideration of production wait time[J]. IEEE Transactions on Reliability, 2016, 65(1):235-247. doi: 10.1109/TR.24 URL
[11]	WU T Y, MA X B, YANG L, et al. Proactive maintenance scheduling in consideration of imperfect repairs and production wait time[J]. Journal of Manufacturing Systems, 2019, 53:183-194. doi: 10.1016/j.jmsy.2019.09.011 URL
[12]	YANG L, ZHAO Y, PENG R, et al. Opportunistic maintenance of production systems subject to random wait time and multiple control limits[J]. Journal of Manufacturing Systems, 2018, 47:12-34. doi: 10.1016/j.jmsy.2018.02.003 URL
[13]	TRUONG B H, 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
[14]	TRUONG B H, CHOLETTE M E, BORGHESANI P, et al. Opportunistic maintenance for wind turbines considering external opportunities—A case study[C]// Proceedings of 3rd International Conference on the Industry 4.0 Model for Advanced Manufacturing. Belgrade, Serbia: Springer, 2018: 211-226.
[15]	PHAM H, WANG H Z. Imperfect maintenance[J]. European Journal of Operational Research, 1996, 94(3):425-438. doi: 10.1016/S0377-2217(96)00099-9 URL
[16]	CINLAR E. Introduction to stochastic processes[M]. Mineola, NY, USA: Dover Publications, Inc., 2013.

i	系统维护活动次数
i	r=1	r=2	r=3	r=4	r=5	r=6	r=7	r=8	r=9
1	1	0	1	0	1	1	0	1	1
2	0	1	0	1	0	1	0	1	1
3	0	1	0	1	0	1	0	1	0
4	0	1	0	1	0	1	0	1	1
5	1	0	1	0	1	1	0	1	1
6	1	0	1	0	1	0	1	1	1
t/h	145.62	160.80	271.41	335.27	426.45	525.55	565.02	718.55	862.85
i	系统维护活动次数
i	r=10	r=11	r=12	r=13	r=14	r=15	r=16	r=17	r=18
1	0	1	0	1	0	1	1	1	0
2	0	1	0	0	1	1	1	0	0
3	1	0	0	1	0	1	0	1	1
4	0	0	1	0	0	1	0	1	0
5	0	1	0	0	1	1	1	1	0
6	0	1	0	0	1	1	1	1	0
t/h	903.84	985.06	1033.36	1065.04	1112.00	1240.07	1346.28	1478.07	1553.55