Product reliability prediction with failure information fusion

Rong Pan, Juan Batres

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

1 Scopus citations

Abstract

A Bayesian statistical approach is proposed to improve product reliability prediction by fusing product failure information from both field performance data and accelerated life testing data. Through this approach a calibration factor is developed, which compensates the difference of failure time distribution when the product is under the operational condition comparing to the lab testing condition. An example, based on the Arrhenius lifetime-stress function of temperature, is used to illustrate how to estimate the calibration, factor as well as other important parameters of the failure time distribution.

Original languageEnglish (US)
Title of host publicationProceedings - 13th ISSAT International Conference on Reliability and Quality in Design
Pages102-106
Number of pages5
StatePublished - Dec 1 2007
Event13th ISSAT International Conference on Reliability and Quality in Design - Seattle, WA, United States
Duration: Aug 2 2007Aug 4 2007

Publication series

NameProceedings - 13th ISSAT International Conference on Reliability and Quality in Design

Other

Other13th ISSAT International Conference on Reliability and Quality in Design
CountryUnited States
CitySeattle, WA
Period8/2/078/4/07

Keywords

  • Accelerated life testing
  • Bayesian method
  • Information fusion
  • Reliability prediction

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality

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  • Cite this

    Pan, R., & Batres, J. (2007). Product reliability prediction with failure information fusion. In Proceedings - 13th ISSAT International Conference on Reliability and Quality in Design (pp. 102-106). (Proceedings - 13th ISSAT International Conference on Reliability and Quality in Design).