DocumentCode :
825519
Title :
An alternative degradation reliability modeling approach using maximum likelihood estimation
Author :
Huang, Wei ; Dietrich, Duane L.
Author_Institution :
Dept. of Syst. & Ind. Eng., Univ. of Arizona, Tucson, AZ, USA
Volume :
54
Issue :
2
fYear :
2005
fDate :
6/1/2005 12:00:00 AM
Firstpage :
310
Lastpage :
317
Abstract :
An alternative degradation reliability modeling approach is presented in this paper. This approach extends the graphical approach used by several authors by considering the natural ordering of performance degradation data using a truncated Weibull distribution. Maximum Likelihood Estimation is used to provide a one-step method to estimate the model´s parameters. A closed form expression of the likelihood function is derived for a two-parameter truncated Weibull distribution with time-independent shape parameter. A semi-numerical method is presented for the truncated Weibull distribution with a time-dependent shape parameter. Numerical studies of generated data suggest that the proposed approach provides reasonable estimates even for small sample sizes. The analysis of fatigue data shows that the proposed approach yields a good match of the crack length mean value curve obtained using the path curve approach and better results than those obtained using the graphical approach.
Keywords :
Weibull distribution; crack detection; fatigue testing; graph theory; maximum likelihood estimation; numerical analysis; reliability theory; closed form expression; crack length mean value curve; degradation reliability modeling approach; maximum likelihood estimation; natural ordering; one-step method; order statistics; path curve approach; performance degradation data; seminumerical method; time-independent shape parameter; truncated Weibull distribution; Data analysis; Degradation; Failure analysis; Fatigue; Maximum likelihood estimation; Parameter estimation; Physics; Shape; Statistical analysis; Weibull distribution; Maximum likelihood estimation; Weibull distribution; order statistics; performance degradation data analysis; reliability modeling;
fLanguage :
English
Journal_Title :
Reliability, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9529
Type :
jour
DOI :
10.1109/TR.2005.845965
Filename :
1435725
Link To Document :
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