Browse > Article

Predicting the future number of failures based on the field failure summary data  

Baik, Jai-Wook (Department of Information Statistics, Korea National Open University)
Jo, Jin-Nam (Department of Information & Statistics, Dongduk Women's University)
Publication Information
Journal of the Korean Data and Information Science Society / v.22, no.4, 2011 , pp. 755-764 More about this Journal
Abstract
In many companies field failure data is used to predict the future number of failures, especially when an unexpected failure mode happens to be a problem. It is because they want to predict the number of spare parts needed and the future quality warranty cost associated with the part based on the predictions of the future number of failures. In this paper field summary data is used to predict the future number of failures based on an appropriate distribution. Other types of data are also investigated to identify the appropriate distribution.
Keywords
Failure summary data; left and right censored data; prediction of future failures; Weibull distribution;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 Jung, K. M. (2008). Optimization of cost and downtime for periodic PM model following the expiration of warranty. Journal of the Korean Data & Information Science Society, 19, 587-596.
2 Lawless, J. F. (1998). Statistical analysis of product warranty data. International Statistical Review, 66, 41-60.   DOI
3 Lawless, J. F., Crowder, M. J. and Hong, Y. (2009). Using accelerated life tests results to predict product field reliability. Technometrics, 51, 146-161.   DOI   ScienceOn
4 Yang, G. (2007). Life cycle reliability engineering, Wiley, Hoboken, NJ.
5 Baik J. W. (2010). The study on the analysis of quality assurance data. Journal of the Korean Data & Information Science Society, 21, 621-628.
6 Baik J. W. and Jo, J. N. (2010). Various types of modelling for scale parameter inWeibull intensity function for two-dimensional warranty data. Journal of the Korean Data & Information Science Society, 21, 555-560.
7 Hong, Y. and Meeker, W. Q. (2010). Field-failure and warrnaty prediction based on auxiliary use-rate information. Technometrics, 52, 148-159.   DOI   ScienceOn
8 Jung, K. M. (2006). Optimal preventive maintenance policy for a repairable system. Journal of the Korean Data & Information Science Society, 17, 367-377.