Copula-based reliability analysis of degrading systems with dependent failures

Guanqi Fang, Rong Pan, Yili Hong

Research output: Contribution to journalArticlepeer-review

101 Scopus citations


Consider a coherent system, in which the degradation processes of its performance characteristics are positively correlated, this paper systematically investigates a bivariate degradation model of such a system. To analyze the accelerated degradation data, a flexible class of bivariate stochastic processes are proposed to incorporate the effects of environmental stress variables and the dependency between two degradation processes is modeled by a copula function. A two-step system reliability analysis approach is developed and it is implemented with the Hamiltonian Monte Carlo algorithm. Simulation studies validate this approach and the consequences of model misspecification are evaluated too. Furthermore, two real-world examples are presented to demonstrate the applicability of the proposed modeling framework of system reliability on correlated degradation processes.

Original languageEnglish (US)
Article number106618
JournalReliability Engineering and System Safety
StatePublished - Jan 2020


  • Accelerated degradation test
  • Bayesian inference
  • Copula function
  • Hamiltonian Monte Carlo
  • Multivariate model
  • System reliability

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering


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