Uncertainty-Aware Dynamic Reliability Analysis Framework for Complex Systems

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

doi:10.1109/access.2018.2843166

Abstract

Critical technological systems exhibit complex dynamic characteristics such as time-dependent behavior, 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 modeling. Quantitative evaluation of DFTs is performed by converting them into generalized 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.

Highlights

Fault tree analysis (FTA) is widely used for safety and reliability analysis of systems
We have considered that the failure rates of the Basic Events (BEs) of the Dynamic fault trees (DFTs) are unknown
There are multiple stochastic and temporal dependencies that need to be taken into account and not all the existing stochastic formalisms are able to grasp these dependencies

Summary

INTRODUCTION

Fault tree analysis (FTA) is widely used for safety and reliability analysis of systems. The contribution of this paper is the proposal of a novel method, which is able to take into account statistical and temporal dependencies in the failure logic as well as uncertainty modelling in component failure data. This approach quantifies complex and dynamic systems accurately taking into account temporal and stochastic dependencies, and it enables the reliability analysis of complex systems with lack of exact failure data of its constituent components.

DYNAMIC FAULT TREE ANALYSIS

NUMERICAL EXAMPLE

H VL M H

CONCLUSION