DocumentCode
1353715
Title
Bayes Inference from Failure Data Contaminated Due to Maintenance
Author
Clarotti, C.A. ; Koch, G. ; Spizzichino, F.
Author_Institution
ENEA TIB-ISP; CRE Casaccia; S.P. Anguillarese 301; 00100 Roma, ITALY.
Issue
4
fYear
1985
Firstpage
377
Lastpage
381
Abstract
In operating plants, records are routinely taken on component-failures, maintenance actions, and component-withdrawals. In some cases, these data are the only available information on the component reliability (proper life-tests being infeasible due to cost, duration or other considerations). For these data to be suitable for inference on the parameters of the underlying life distributions, one has to account for the homogeneity-constraints on the stopping rules and the effect of maintenance. We generalize the sampling plan proposed by Barlow & Proschan for coping with incomplete data obtained under non-homogeneous stopping-rules, by allowing components to be maintained. A Bayes model accounts for the effect of maintenance.
Keywords
Aging; Contamination; Costs; Preventive maintenance; Random variables; Reliability theory; Sampling methods; State estimation; Statistical distributions; Testing; Component age; Data contamination; Field data; IFR distribution; Incomplete sample; Non-informative stopping rule;
fLanguage
English
Journal_Title
Reliability, IEEE Transactions on
Publisher
ieee
ISSN
0018-9529
Type
jour
DOI
10.1109/TR.1985.5222199
Filename
5222199
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