A Bayesian Integrated Reliability Analysis of Locomotive Wheels (贝叶斯方法在机车车轮可靠性退化分析中的应用)

Jing Lin
Dr. Jing Lin is currently an Assistant Professor in the Division of Operation and Maintenance Engineering, at Luleå University of Technology (LTU), Sweden. She received her PhD degree in Management Science from Nanjing University of Science and Technology, China. After the college, she worked three years for SKF Co., Ltd as an Asset Management Consultant for industries. Dr. Lin’s current resear...read more


This presentation aims to show a study on propose, develop and test an integrated reliability analysis for railway industry, by which to support decision making on maintenance strategies optimization. This integrated analysis applies traditional statistics theories as well as Bayesian statistics using Markov Chain Monte Carlo (MCMC) methodologies. In this study, the integrated procedure for Bayesian reliability inference using MCMC is applied to a number of case studies using locomotive wheel degradation data from Iron Ore Line (Malmbanan), Sweden. The research explores the impact of a locomotive wheel’s installed position on its service lifetime and attempts to predict its reliability characteristics by using parametric models, non-parametric models, frailty factors, etc.

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