A general preventive maintenance framework of a production system considering dynamic maintenance accessibility

被引:1
作者
Zhao, Fei [1 ,2 ]
Zhang, Nan [3 ,4 ]
机构
[1] Northeastern Univ, Sch Business Adm, Shenyang, Peoples R China
[2] Northeastern Univ Qinhuangdao, Qinhuangdao, Peoples R China
[3] Beijing Inst Technol, Sch Management, Beijing, Peoples R China
[4] Beijing Inst Technol, State Key Lab Explos Sci & Safety Protect, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Maintenance; Dynamic environment; Maintenance delay; Accessibility constraint; Stochastic optimization; RELIABILITY; OPTIMIZATION; DEGRADATION; STRATEGIES; MODELS; POLICY;
D O I
10.1016/j.cie.2025.111054
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, we investigate the maintenance problem of a production system where maintenance delay and dynamic environmental accessibility are considered. The system can be a single-component system or a series system with multiple components. It operates in a dynamic environment modeled by a discrete time Markov chain. The impact of the environment is twofold. Both the system productivity and the maintenance process depend on the environment state. Maintenance delay is taken into account in this work, such that the maintenance crew needs non-negligible times to arrive for maintenance activity. In addition, maintenance executing times are also non-negligible. We propose a preventive maintenance framework for a general production system. The component(s) are aging with time, described by their degradation levels or the time elapsed since their last renewal epochs, depending on their failure characteristics. For a specific maintenance scheduling, some reliability and production measure indexes such as the availability, environmental accessibility ratio and production loss rate are proposed to assess the system characteristics. The maintenance cost in the long-run horizon is also derived. We solve these problems in the framework of a semi-regenerative process. To further illustrate the properties of the policy, we show how the model is adaptive to single-component systems in detail. An example concerning a two-component production system is also presented. The model can provide theoretical references for decision-makers when maintenance delay and dynamic maintenance accessibility needs to be taken into account.
引用
收藏
页数:10
相关论文
共 42 条
[1]   A review on condition-based maintenance optimization models for stochastically deteriorating system [J].
Alaswad, Suzan ;
Xiang, Yisha .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2017, 157 :54-63
[2]  
Banjevic D., 2006, IMA Journal of Management Mathematics, V17, P115, DOI 10.1093/imaman/dpi029
[3]   Joint condition-based maintenance and load-sharing optimization for two-unit systems with economic dependency [J].
Broek, Michiel A. J. Uit Het ;
Teunter, Ruud H. ;
de Jonge, Bram ;
Veldman, Jasper .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2021, 295 (03) :1119-1131
[4]   Joint condition-based maintenance and condition-based production optimization [J].
Broek, Michiel A. J. Uit Het ;
Teunter, Ruud H. ;
de Jonge, Bram ;
Veldman, Jasper .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2021, 214
[5]   Season-Dependent Condition-Based Maintenance for a Wind Turbine Using a Partially Observed Markov Decision Process [J].
Byon, Eunshin ;
Ding, Yu .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2010, 25 (04) :1823-1834
[6]   Optimal Maintenance Strategies for Wind Turbine Systems Under Stochastic Weather Conditions [J].
Byon, Eunshin ;
Ntaimo, Lewis ;
Ding, Yu .
IEEE TRANSACTIONS ON RELIABILITY, 2010, 59 (02) :393-404
[7]   Condition-based maintenance using the inverse Gaussian degradation model [J].
Chen, Nan ;
Ye, Zhi-Sheng ;
Xiang, Yisha ;
Zhang, Linmiao .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2015, 243 (01) :190-199
[8]   Degradation Modeling Based on a Time-Dependent Ornstein-Uhlenbeck Process and Residual Useful Lifetime Estimation [J].
Deng, Yingjun ;
Barros, Anne ;
Grall, Antoine .
IEEE TRANSACTIONS ON RELIABILITY, 2016, 65 (01) :126-140
[9]  
DOWNTON F, 1970, J ROY STAT SOC B, V32, P408
[10]   SHOCK MODELS AND WEAR PROCESSES [J].
ESARY, JD ;
MARSHALL, AW ;
PROSCHAN, F .
ANNALS OF PROBABILITY, 1973, 1 (04) :627-649