Bayesian Accelerated Reliability Growth of Complex Systems

Cesar Ruiz, Haitao Liao, Ed Pohl, Kelly M. Sullivan

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

6 Scopus citations


Today's competitive global business environment and continually increasing product complexity have created a need to shorten product development time while guaranteeing high reliability for customers. In this context, reliability growth programs and accelerated life testing (ALT) have become the tools of choice to help companies achieve their product reliability goals as fast as possible. One of the most popular statistical models for analyzing reliability growth data is the Crow-AMSAA model, which struggles to incorporate ALT data when the product has multiple failure modes. Moreover, key system components may be developed independently and without incorporating the testing results in the product reliability estimation. Thus, companies may be performing unnecessary testing at the system level.

Original languageEnglish (US)
Title of host publication2018 Annual Reliability and Maintainability Symposium, RAMS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538628706
StatePublished - Sep 11 2018
Event2018 Annual Reliability and Maintainability Symposium, RAMS 2018 - Reno, United States
Duration: Jan 22 2018Jan 25 2018

Publication series

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


Other2018 Annual Reliability and Maintainability Symposium, RAMS 2018
Country/TerritoryUnited States


  • Accelerated Life Testing
  • Bayesian Statistics
  • Reliability Growth

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • General Mathematics
  • Computer Science Applications


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