Joint modeling of preventive maintenance and quality improvement for deteriorating single-machine manufacturing systems

被引:64
作者
Lu, Biao [1 ]
Zhou, Xiaojun [1 ]
Li, Yanting [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Mech Engn, Dept Ind Engn & Management, 800 Dong Chuan Rd, Shanghai 200240, Peoples R China
基金
中国国家自然科学基金; 上海市自然科学基金;
关键词
Manufacturing system; Preventive maintenance; Quality improvement; Response model; Reliability modeling; Cost optimization; STATISTICAL PROCESS-CONTROL; INTEGRATED MODEL; CONTROL CHART; OPTIMIZATION; POLICY;
D O I
10.1016/j.cie.2015.11.019
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
For a deteriorating single-machine manufacturing system, preventive maintenance (PM) is an effective way to improve the machine reliability and product quality. In conventional PM models, however, quality improvement has been seldom considered, which may lead to loss of economic benefits. In this paper, a joint model is proposed, in which quality improvement is integrated into PM decision-making. In the proposed model, process variables affecting product quality are identified, among which adjustable process variables are measures of the degradation states of quality-related components of the machine. Based on the response model, a process model is developed to quantitatively describe the impact of process variables on product quality. An integrated reliability model is built for the machine based on the proportional hazard model considering the effects of the degradation states of quality-related components on machine reliability. Quality loss is incorporated into the total cost, which is minimized to obtain the optimal PM schedule. A case study is conducted to illustrate the effectiveness of the joint model. It shows that the joint model can achieve a superior economic performance to the conventional PM model in general case. Economic benefits can be created by integrating quality improvement into PM decision-making. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:188 / 196
页数:9
相关论文
共 31 条
[21]   Tool maintenance optimization for multi-station machining systems with economic consideration of quality loss and obsolescence [J].
Sun Ji-wen ;
Xi Li-feng ;
Du Shi-chang ;
Pan Er-shun .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2010, 26 (02) :145-155
[22]   AN INTEGRATED COST MODEL FOR THE JOINT OPTIMIZATION OF PROCESS-CONTROL AND MAINTENANCE [J].
TAGARAS, G .
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 1988, 39 (08) :757-766
[23]   Machine performance degradation assessment and remaining useful life prediction using proportional hazard model and support vector machine [J].
Van Tung Tran ;
Hong Thom Pham ;
Yang, Bo-Suk ;
Tan Tien Nguyen .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2012, 32 :320-330
[24]  
Vlok PJ, 2002, J OPER RES SOC, V53, P193, DOI 10.1057/palgrave.jors.2601261
[25]   A simulation-based multivariate Bayesian control chart for real time condition-based maintenance of complex systems [J].
Wang, Wenbin .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2012, 218 (03) :726-734
[26]   Modeling and optimizing maintenance schedule for energy systems subject to degradation [J].
Xia, Tangbin ;
Xi, Lifeng ;
Zhou, Xiaojun ;
Du, Shichang .
COMPUTERS & INDUSTRIAL ENGINEERING, 2012, 63 (03) :607-614
[27]   Joint optimization of (X)over-bar control chart and preventive maintenance policies: A discrete-time Markov chain approach [J].
Xiang, Yisha .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2013, 229 (02) :382-390
[28]   An integrated model of statistical process control and maintenance based on the delayed monitoring [J].
Yin, Hui ;
Zhang, Guojun ;
Zhu, Haiping ;
Deng, Yuhao ;
He, Fei .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2015, 133 :323-333
[29]   Control-limit preventive maintenance policies for components subject to imperfect preventive maintenance and variable operational conditions [J].
You, Ming-Yi ;
Li, Hongguang ;
Meng, Guang .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2011, 96 (05) :590-598
[30]   A condition-based maintenance strategy for heterogeneous populations [J].
Zhang, Mimi ;
Ye, Zhisheng ;
Xie, Min .
COMPUTERS & INDUSTRIAL ENGINEERING, 2014, 77 :103-114