A bayesian approach for system reliability analysis with multilevel pass-fail, lifetime and degradation data sets

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Author(s)

  • Weiwen Peng
  • Hong-Zhong Huang
  • Min Xie
  • Yuanjian Yang
  • Yu Liu

Detail(s)

Original languageEnglish
Article number6550896
Pages (from-to)689-699
Journal / PublicationIEEE Transactions on Reliability
Volume62
Issue number3
Online published2 Jul 2013
Publication statusPublished - Sept 2013

Abstract

Reliability analysis of complex systems is a critical issue in reliability engineering. Motivated by practical needs, this paper investigates a Bayesian approach for system reliability assessment and prediction with multilevel heterogeneous data sets. Two major imperatives have been handled in the proposed approach, which provides a comprehensive Bayesian framework for the integration of multilevel heterogeneous data sets. In particular, the pass-fail data, lifetime data, and degradation data at different system levels are combined coherently for system reliability analysis. This approach goes beyond the alternatives that deal with solely multilevel pass-fail or lifetime data, and presents a more practical tool for real engineering applications. In addition, the indices for reliability assessment and prediction are constructed coherently within the proposed Bayesian framework. It gives rise to a natural manner of incorporating this approach into a decision-making procedure for system operation and management. The effectiveness of the proposed approach is illustrated with reliability analysis of a navigation satellite. © 2013 IEEE.

Research Area(s)

  • Bayesian reliability, multilevel heterogeneous data sets (MHDS), reliability assessment, reliability prediction

Citation Format(s)

A bayesian approach for system reliability analysis with multilevel pass-fail, lifetime and degradation data sets. / Peng, Weiwen; Huang, Hong-Zhong; Xie, Min et al.
In: IEEE Transactions on Reliability, Vol. 62, No. 3, 6550896, 09.2013, p. 689-699.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review