Articles:2018,Vol:23,Issue(2):89-96
Citation:
JIANG Renyan, CHEN Hao. Model for Failure Point Process of a Repairable System and Application[J]. International Journal of Plant Engineering and Management, 2018, 23(2): 89-96

Model for Failure Point Process of a Repairable System and Application
JIANG Renyan, CHEN Hao
Faculty of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China
Abstract:
A engineering system is usually repairable, and failure process of a repairable system is often described by a failure point process. The power law model is a commonly used approach to model the failure point process. This paper introduces the concept and model for the failure process of repairable system. The method of parameter estimation is developed, and failure observations are fitted into a power-law model by using the least square method. Two applications of the pressent model are discussed according to the practical failure data of the central cooling system of a nuclear power plant. One application is determining the optimal overhaul time, and the other is evaluating the quality of maintenance. This paper provides references for the overhaul decision making and maintenance quality evaluation in reality.
Key words:    repairable system    failure point process    overhaul decision    maintenance quality   
Received: 2017-12-26     Revised:
DOI: 10.13434/j.cnki.1007-4546.2018.0204
Funds: This paper is supported by the National Natural Science Foundation of China (71771029)
Corresponding author:     Email:
Author description: JIANG Renyan is a professor in Faculty of Automotive and Mechanical Engineering, Changsha University of Science and Technology. His research interests are reliability engineering, quality engineering and maintenance theory. jiang@csust.edu.cn
CHEN Hao is a student in Faculty of Automotive and Mechanical Engineering, Changsha University of Science and Technology. Her research interests are reliability engineering, quality engineering and maintenance theory. chenhao9401@qq.com
Service
PDF(161KB) Free
Print
Authors
JIANG Renyan
CHEN Hao

References:
[1] Jiang R. Introduction to quality and reliability engineering[M]. London:Springer & Beijing:Science Press, 2015
[2] Jiang R, Murthy DNP. Maintenance:decision models for management[M]. Beijing:Science Press, 2008
[3] Thompson W A. Point process models with applications to safety and reliability[M].New York:Chapman and Hall, 1988
[4] Kvaløy J T, Bo H L. TTT-based tests for trend in repairable systems data[J]. Reliability Engineering System Safety, 1998, 60:13-28
[5] Jiang R Y, Zhou Y. Failure-counting based health evaluation of a bus fleet[C]//Prognostics and Health Management Conference. IEEE, 2010:1-4
[6] Nelson W. An application of graphical analysis of repair data[J]. Quality and Reliability Engineering International, 1998, 14(1):49-52
[7] Jiang R Y, Yu Q. Comparison analysis of two cost rate models for age replacement policy[J]. Mechanical Science and Technology for Aeroapace Engineering, 2016, 35(6):951-955(in Chinese)
[8] Basu A P, Rigdon S E. Statistical methods for the reliability of repairable systems[M]. Statistical Methods for the Reliability of Repairable Systems, Wiley, 2000:652-653
[9] Bo H L. On the statistical modeling and analysis of repairable systems[J]. Quality Control & Applied Statistics, 2007, 53(4):97-100
[10] Zhang G F, Jiang R Y. Evaluation of the effect of preventive maintenance for urban bus using the change point method[J]. Journal of Transport Science and Engineering, 2010, 26(3):71-76(in Chinese)
[11] Mahmood S, Maxim F, Ming J Z. Optimal burn-in and preventive maintenance warranty strategies with time-dependent maintenance costs[J]. Iie Transactions, 2013, 45(9):1024-1033
[12] Pulcini G. Modeling the failure data of a repairable equipment with bathtub type failure intensity[J]. Reliability Engineering & System Safety, 2001, 71(2):209-218
[13] Leemis L M. Nonparametric estimation of the cumulative intensity function for a nonhomogeneous poisson process[J]. Management Science, 1991, 37(7):886-900
[14] Arkin B L, Leemis L M. Nonparametric estimation of the cumulative intensity function for a nonhomogeneous poisson process from overlapping realizations[M]. INFORMS, 2000
[15] Jiang R Y, Guo Y. Estimating failure intensity of a repairable system to decide on its preventive maintenance or retirement[J]. International Journal of Performability Engineering, 2014, 10(6):577-588
[16] Jiang R Y. Estimating residual life distribution from fractile curves of a condition variable[C]//Prognostics and System Health Management Conference. IEEE, 2016:1-6
[17] Shin I, Lim T J, Lie C H. Estimating parameters of intensity function and maintenance effect for repairable unit[J]. Reliability Engineering and System Safety, 1996, 54:1-10