DocumentCode :
1395748
Title :
Fitting the Weibull log-linear model to accelerated life-test data
Author :
Wang, Wendai ; Kececioglu, Dimitri B.
Author_Institution :
Dept. of Res. & Dev., GE Corp., Niskayuna, NY, USA
Volume :
49
Issue :
2
fYear :
2000
fDate :
6/1/2000 12:00:00 AM
Firstpage :
217
Lastpage :
223
Abstract :
The Weibull log-linear model is a widely-used accelerated life-test model in reliability engineering. The standard deviation of log(life), s, was often assumed to be a constant or stress-independent. However, theoretical and experimental research results suggest that, in many cases, s is stress-dependent. The data analysis via the MLE method must be performed numerically, because of the complexity of the model and many unknown parameters being involved. The commonly-used methods often fail to converge when the starting point is not close to the solution, especially for censored data. Generally, no easy-to-use software is available for the Weibull log-linear model. To facilitate this process, an efficient algorithm is presented in this paper, to obtain the MLE of the model parameters from test data (with or without censoring) for both stress-independent and stress-dependent models. The validity and effectiveness of this procedure are illustrated with numerical examples. The method is numerically stable, and easy to implement and program
Keywords :
Weibull distribution; least squares approximations; life testing; log normal distribution; maximum likelihood estimation; MLE method; Weibull log-linear model; Weibull log-linear model fitting; accelerated life-test data; censored data; data analysis; generalised linear model; log life standard deviation; maximum likelihood estimation; proportional hazards; stress-dependent models; stress-independent models; weighted least squares; Acceleration; Data analysis; Hazards; Least squares approximation; Life estimation; Life testing; Maximum likelihood estimation; Prognostics and health management; Reliability engineering; Stress;
fLanguage :
English
Journal_Title :
Reliability, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9529
Type :
jour
DOI :
10.1109/24.877341
Filename :
877341
Link To Document :
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