上海交通大学学报 ›› 2021, Vol. 55 ›› Issue (10): 1281-1290.doi: 10.16183/j.cnki.jsjtu.2020.320
所属专题: 《上海交通大学学报》2021年12期专题汇总专辑; 《上海交通大学学报》2021年“工业工程与管理”专题
收稿日期:
2020-10-09
出版日期:
2021-10-28
发布日期:
2021-11-01
通讯作者:
周晓军
E-mail:zzhou745@sjtu.edu.cn
作者简介:
宁小涵(1997-),女,辽宁省沈阳市人,硕士生,主要从事设备维护决策研究.
基金资助:
Received:
2020-10-09
Online:
2021-10-28
Published:
2021-11-01
Contact:
ZHOU Xiaojun
E-mail:zzhou745@sjtu.edu.cn
摘要:
为了充分利用由外部因素如原材料不足或需求不足等导致的随机生产等待带来的维护机会,针对多设备串行生产系统,引入质心与引力窗概念,提出一种时间窗与引力窗相结合的机会维护决策优化模型,同时考虑设备强制预防维护引发的内部维护机会和生产等待带来的外部维护机会,以最小化规划期内系统的维护总成本率为目标,获取最优维护策略.算例分析表明,时间窗与引力窗相结合的建模方法在降低维护总成本方面有明显优势,可有效解决生产等待的到达及持续时间的不确定性问题.
中图分类号:
宁小涵, 周晓军. 考虑随机生产等待的串行生产系统机会维护建模[J]. 上海交通大学学报, 2021, 55(10): 1281-1290.
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.
表1
设备参数
i | | | | | | αi | βi | θi |
---|---|---|---|---|---|---|---|---|
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 |
表2
系统维护时刻表
i | 系统维护活动次数 | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
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 | |||||||||
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 |
表3
不同停机成本的仿真结果
κ | | F*/kN | c | c | c | 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 |
表4
不同生产等待到达频率的仿真结果
λ/(次·h-1) | Twin*/h | F*/kN | c | c | c | 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 |
[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. |
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