Premium
Reliability Estimation for Accelerated Life Tests Based on a Cox Proportional Hazard Model with Error Effect
Author(s) -
RodríguezBorbón Manuel Iván,
RodríguezMedina Manuel Arnoldo,
RodríguezPicón Luis Alberto,
AlvaradoIniesta Alejandro,
Sha Naijun
Publication year - 2017
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/qre.2113
Subject(s) - weibull distribution , accelerated life testing , reliability (semiconductor) , statistics , markov chain monte carlo , bayesian probability , bayesian inference , reliability engineering , hazard , computer science , mathematics , engineering , power (physics) , physics , chemistry , organic chemistry , quantum mechanics
In this paper, a Cox proportional hazard model with error effect applied on the study of an accelerated life test is investigated. Statistical inference under Bayesian methods by using the Markov chain Monte Carlo techniques is performed in order to estimate the parameters involved in the model and predict reliability in an accelerated life testing. The proposed model is applied to the analysis of the knock sensor failure time data in which some observations in the data are censored. The failure times at a constant stress level are assumed to be from a Weibull distribution. The analysis of the failure time data from an accelerated life test is used for the posterior estimation of parameters and prediction of the reliability function as well as the comparisons with the classical results from the maximum likelihood estimation. Copyright © 2017 John Wiley & Sons, Ltd.