A general Bayes weibull inference model for accelerated life testing

René Van Dorp, J. and Thomas A. Mazzuchi

Reliability Engineering and System Safety, 2005, vol. 90, issue 2, 140-147

Abstract: This article presents the development of a general Bayes inference model for accelerated life testing. The failure times at a constant stress level are assumed to belong to a Weibull distribution, but the specification of strict adherence to a parametric time-transformation function is not required. Rather, prior information is used to indirectly define a multivariate prior distribution for the scale parameters at the various stress levels and the common shape parameter. Using the approach, Bayes point estimates as well as probability statements for use-stress (and accelerated) life parameters may be inferred from a host of testing scenarios. The inference procedure accommodates both the interval data sampling strategy and type I censored sampling strategy for the collection of ALT test data. The inference procedure uses the well-known MCMC (Markov Chain Monte Carlo) methods to derive posterior approximations. The approach is illustrated with an example.

Keywords: Dirichlet distribution; Environmental testing; Step-stress testing (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:90:y:2005:i:2:p:140-147

DOI: 10.1016/j.ress.2004.10.012

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