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Reliability Analysis for Degradation of Locomotive Wheels using Parametric Bayesian Approach
Author(s) -
Lin Jing,
Asplund Matthias,
Parida Aditya
Publication year - 2014
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.1518
Subject(s) - bayesian probability , reliability (semiconductor) , weibull distribution , engineering , parametric statistics , bayesian linear regression , diesel locomotive , bogie , regression analysis , position (finance) , bayesian inference , reliability engineering , statistics , automotive engineering , mathematics , structural engineering , power (physics) , physics , finance , quantum mechanics , economics
This paper undertakes a reliability study using a Bayesian survival analysis framework to explore the impact of a locomotive wheel's installed position on its service lifetime and to predict its reliability characteristics. The Bayesian Exponential Regression Model, Bayesian Weibull Regression Model and Bayesian Log‐normal Regression Model are used to analyze the lifetime of locomotive wheels using degradation data and taking into account the position of the wheel. This position is described by three different discrete covariates: the bogie, the axle and the side of the locomotive where the wheel is mounted. The goal is to determine reliability, failure distribution and optimal maintenance strategies for the wheel. The results show that: (i) under specified assumptions and a given topography, the position of the locomotive wheel could influence its reliability and lifetime; (ii) the Bayesian Log‐normal Regression Model is a useful tool. Copyright © 2013 John Wiley & Sons, Ltd.