Title :
A cautionary tale about Weibull analysis [reliability estimation]
Author :
Mackisack, M.S. ; Stillman, R.H.
Author_Institution :
Queensland Univ., Qld., Australia
fDate :
6/1/1996 12:00:00 AM
Abstract :
This paper makes three points about possible perils of unguarded fitting of Weibull distributions to data: (1) bias is introduced by incomplete data, which may have counter-intuitive effects; (2) bias is introduced into percentile estimates by using regression on log-transformed variables to fit the Weibull parameters, particularly if the percentile to be predicted lies outside the range of the data; and (3) the amount of variation associated with such estimates can be very substantial. A partial solution to the incomplete data problem using simulation is presented, and the maximum likelihood approach to parameter estimation and its advantages relative to regression estimation are explained. The problem arose in predicting life expectancy of long-lived components subject to natural aging which cannot be investigated using accelerated testing and for which the collection of data provides an incomplete life record
Keywords :
Weibull distribution; ageing; failure analysis; maximum likelihood estimation; parameter estimation; reliability theory; statistical analysis; Weibull analysis; life expectancy prediction; log-transformed variables regression; maximum likelihood approach; natural aging; parameter estimation; percentile estimates; regression estimation; reliability estimation; unguarded data fitting; Accidents; Copper; Costing; Data analysis; Degradation; Life estimation; Maximum likelihood estimation; Parameter estimation; Predictive models; Weibull distribution;
Journal_Title :
Reliability, IEEE Transactions on