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
[1]   An overview of time-based and condition-based maintenance in industrial application [J].
Ahmad, Rosmaini ;
Kamaruddin, Shahrul .
COMPUTERS & INDUSTRIAL ENGINEERING, 2012, 63 (01) :135-149
[2]  
Allen TT., 2006, INTRO ENG STAT 6 SIG
[3]  
[Anonymous], 1987, Introduction to Quality Engineering: Designing Quality into Products and Processes
[4]  
[Anonymous], 2010, ENG ASSET LIFECYCLE
[5]   Combining preventive maintenance and statistical process control: a preliminary investigation [J].
Cassady, CR ;
Bowden, RO ;
Liew, L ;
Pohl, EA .
IIE TRANSACTIONS, 2000, 32 (06) :471-478
[6]   Minimizing the cost of integrated systems approach to process control and maintenance model by EWMA control chart using genetic algorithm [J].
Charongrattanasakul, P. ;
Pongpullponsak, A. .
EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (05) :5178-5186
[7]   Quality-oriented-maintenance for multiple interactive tooling components in discrete manufacturing processes [J].
Chen, Y ;
Jin, JH .
IEEE TRANSACTIONS ON RELIABILITY, 2006, 55 (01) :123-134
[8]   A bivariate optimal imperfect preventive maintenance policy for a used system with two-type shocks [J].
Chen, Yen-Luan .
COMPUTERS & INDUSTRIAL ENGINEERING, 2012, 63 (04) :1227-1234
[9]   Joint optimal production control/preventive maintenance policy for imperfect process manufacturing cell [J].
Dhouib, K. ;
Gharbi, A. ;
Ben Aziza, M. N. .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2012, 137 (01) :126-136
[10]   Maintenance policy optimization-literature review and directions [J].
Ding, Siew-Hong ;
Kamaruddin, Shahrul .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2015, 76 (5-8) :1263-1283