A Bayesian generalized Eyring-Weibull accelerated life testing model

被引：4

作者：

Smit, Neill ^{[1
]}

Raubenheimer, Lizanne ^{[2
]}

Mazzuchi, Thomas ^{[3
]}

Soyer, Refik ^{[4
]}

机构：

[1] North West Univ, Ctr Business Math & Informat, Potchefstroom, South Africa

[2] Rhodes Univ, Dept Stat, Makhanda, South Africa

[3] George Washington Univ, Dept Engn Management & Syst Engn, Washington, DC USA

[4] George Washington Univ, Dept Decis Sci, Washington, DC USA

来源：

QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL | 2024年 / 40卷 / 02期

基金：

新加坡国家研究基金会;

关键词：

accelerated life testing; Bayes; generalized Eyring model; Markov chain Monte Carlo; Weibull distribution; INFERENCE MODEL; PROBABILITY; SIMULATION; SCALE;

D O I：

10.1002/qre.3458

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In this paper, a novel approach to a Bayesian accelerated life testing model is presented. The Weibull distribution is used as the life distribution and the generalized Eyring model as the time transformation function. This is a model that allows for the use of more than one stressor, whereas other commonly used acceleration models, such as the Arrhenius and power law models, incorporate one stressor. The use of the generalized Eyring-Weibull model developed in this paper is demonstrated in a case study, where Markov chain Monte Carlo methods are utilized to generate samples for posterior inference.

引用

收藏

页码：1110 / 1125

页数：16

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