Regression models for parameters related to Bayesian reliability inference procedures

Peng Wang, Tongdan Jin, Haitao Liao, Jiachen Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper proposes a regression model for estimating Bayesian parameters related to reliability point and interval estimations. It is demonstrated that, using these regression models, reliability predictions can be made efficiently based on limited available testing data. Reliability estimation using traditional approaches generally considers electronic system failure rates as fixed but unknown constants, which can be estimated from sample test data taken randomly from the population. Prior knowledge is not used. Bayesian reliability inference, on the other hand, considers the failure rates as random, not fixed, quantities. Bayesian methods allow the incorporation of one's prior knowledge into the estimating process. Combining one's prior knowledge and limited testing results, reliability can be estimated more effectively. However, Bayesian reliability analysis has not been extensively applied in industry. One major reason is the complexity of the procedure and the computational intensity involved. In this paper, empirical regression models are developed to estimate the parameters related to Bayesian reliability point and interval estimation procedures.

Original languageEnglish (US)
Title of host publicationProceeding of 2005 International Conference on Asian Green Electronics- Design for Manufacturability and Reliability, 2005AGEC
Pages167-171
Number of pages5
DOIs
StatePublished - Dec 1 2005
Event2005 International Conference on Asian Green Electronics- Design for Manufacturability and Reliability, 2005AGEC - Shanghai, China
Duration: Mar 15 2005Mar 18 2005

Publication series

NameProceeding of 2005 International Conference on Asian Green Electronics- Design for Manufacturability and Reliability, 2005AGEC
Volume2005

Other

Other2005 International Conference on Asian Green Electronics- Design for Manufacturability and Reliability, 2005AGEC
CountryChina
CityShanghai
Period3/15/053/18/05

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Wang, P., Jin, T., Liao, H., & Liu, J. (2005). Regression models for parameters related to Bayesian reliability inference procedures. In Proceeding of 2005 International Conference on Asian Green Electronics- Design for Manufacturability and Reliability, 2005AGEC (pp. 167-171). [1452339] (Proceeding of 2005 International Conference on Asian Green Electronics- Design for Manufacturability and Reliability, 2005AGEC; Vol. 2005). https://doi.org/10.1109/AGEC.2005.1452339