Uncertainty-aware dynamic reliability analysis framework for complex systems

Sohag Kabir, Mohammad Yazdi, Jose Ignacio Aizpurua, Yiannis Papadopoulos

Research output: Contribution to journalArticlepeer-review

69 Citations (Scopus)
54 Downloads (Pure)


Critical technological systems exhibit complex dynamic characteristics such as time-dependent behaviour, functional dependencies among events, sequencing and priority of causes that may alter the effects of failure. Dynamic fault trees (DFTs) have been used in the past to model the failure logic of such systems, but the quantitative analysis of DFTs has assumed the existence of precise failure data and statistical independence among events, which are unrealistic assumptions. In this paper, we propose an improved approach to reliability analysis of dynamic systems, allowing for uncertain failure data and statistical and stochastic dependencies among events. In the proposed framework, DFTs are used for dynamic failure modelling. Quantitative evaluation of DFTs is performed by converting them into generalised stochastic Petri nets. When failure data are unavailable, expert judgment and fuzzy set theory are used to obtain reasonable estimates. The approach is demonstrated on a simplified model of a Cardiac Assist System.
Original languageEnglish
JournalIEEE Access
Early online date7 Jun 2018
Publication statusE-pub ahead of print - 7 Jun 2018


  • dynamic systems
  • fault tree analysis
  • fuzzy set theory
  • petri nets
  • reliability analysis


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