A life prediction approach based on integrated failure information

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper a Bayesian method is introduced to evaluate products' life by integrating the failure information in field and prior failure information collected from various sources. Calibrators are used to calibrate the difference between failure information in field and prior failure information, then Bayesian approach can be used to integrate failure data. The posterior distributions of unknown parameters can be obtained through statistical inference procedure, which is carried out through Markov chain and Monte Carlo (MCMC) method. Normal distribution and 2-parameters Weibull distribution are discussed based on the fusion model established, and simulation examples are performed to illustrate the use of proposed method. The orthogonal analysis shows the influence of different chosen values to prior means of unknown parameters on prediction results.

Original languageEnglish
Title of host publicationRAMS 2014 - Proceedings 2014
Subtitle of host publicationThe 60th Annual Reliability and Maintainability Symposium
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479928477
DOIs
StatePublished - 2014
Event60th Annual Reliability and Maintainability Symposium, RAMS 2014 - Colorado Springs, CO, United States
Duration: 27 Jan 201430 Jan 2014

Publication series

NameProceedings - Annual Reliability and Maintainability Symposium
ISSN (Print)0149-144X

Conference

Conference60th Annual Reliability and Maintainability Symposium, RAMS 2014
Country/TerritoryUnited States
CityColorado Springs, CO
Period27/01/1430/01/14

Keywords

  • Bayesian inference
  • MCMC method
  • failure information model
  • life prediction

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