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Estimation of time‐to‐failure distribution derived from a degradation model using fuzzy clustering
Author(s) -
Wu ShuoJye,
Tsai TzongRu
Publication year - 2000
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/1099-1638(200007/08)16:4<261::aid-qre333>3.0.co;2-3
Subject(s) - cluster analysis , degradation (telecommunications) , fuzzy logic , computer science , data mining , statistics , fuzzy clustering , mathematics , econometrics , artificial intelligence , telecommunications
Some life tests are terminated with few or no failures. In such cases, a recent approach is to obtain degradation measurements of product performance that may contain some useful information about product reliability. Generally degradation paths of products are modeled by a nonlinear regression model with random coefficients. If we can obtain the estimates of parameters under the model, then the time‐to‐failure distribution can be estimated. In some cases, the patterns of a few degradation paths are different from those of most degradation paths in a test. Therefore, this study develops a weighted method based on fuzzy clustering procedure to robust estimation of the underlying parameters and time‐to‐failure distribution. The method will be studied on a real data set. Copyright © 2000 John Wiley & Sons, Ltd.