上海交通大学学报

上海交通大学学报 >

2021 , Vol. 55 >Issue 10: 1281 - 1290

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2020.320

考虑随机生产等待的串行生产系统机会维护建模

展开
  • 上海交通大学 机械与动力工程学院,上海 200240
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.

收稿日期: 2020-10-09

  网络出版日期: 2021-11-01

基金资助

国家自然科学基金(52075336);科技部重点研发计划(2020YFB1711103)

收起

Opportunistic Maintenance Modeling for Serial Production Systems with Stochastic Production Waits

Expand
  • School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received date: 2020-10-09

  Online published: 2021-11-01

Fold

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.

关键词： 多设备串行系统; 生产等待; 机会维护; 维护时间窗; 维护引力窗

本文引用格式

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 . DOI: 10.16183/j.cnki.jsjtu.2020.320

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

参考文献

[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.
[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.
[2] 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.
[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.
[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.
[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.
[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.
[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.
[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.
[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.
[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.
[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.
[16] CINLAR E. Introduction to stochastic processes[M]. Mineola, NY, USA: Dover Publications, Inc., 2013.
Options
文章导航

/

〈 〉