Skip to main content

Research Repository

Advanced Search

Uncertainty-aware dynamic reliability analysis framework for complex systems

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


Sohag Kabir

Mohammad Yazdi

Jose Ignacio Aizpurua


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.


Kabir, S., Yazdi, M., Aizpurua, J. I., & Papadopoulos, Y. (2018). Uncertainty-aware dynamic reliability analysis framework for complex systems. IEEE Access, 6, Article ACCESS2843166.

Acceptance Date May 27, 2018
Online Publication Date Jun 7, 2018
Publication Date Jun 7, 2018
Deposit Date Jun 8, 2018
Publicly Available Date Apr 17, 2023
Journal IEEE Access
Electronic ISSN 2169-3536
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 6
Article Number ACCESS2843166
Keywords Dynamic Systems; Fault Tree Analysis; Reliability Analysis; Safety Analysis; Fuzzy set theory; Petri nets; Probabilistic Risk Assessment; Uncertainty Analysis; Decision under uncertainty
Public URL
Publisher URL


Article (1.1 Mb)

Copyright Statement
(c) 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See<br /> for more information.

You might also like

Downloadable Citations