A Hybrid Modular Approach for Dynamic Fault Tree Analysis

Sohag Kabir,Yiannis Papadopoulos,Koorosh Aslansefat,Savas Konur,Ioannis Sorokos

doi:10.1109/access.2020.2996643

Sohag Kabir, Yiannis Papadopoulos + Show 3 more

Open Access

https://doi.org/10.1109/access.2020.2996643

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Abstract

Over the years, several approaches have been developed for the quantitative analysis of dynamic fault trees (DFTs). These approaches have strong theoretical and mathematical foundations; however, they appear to suffer from the state-space explosion and high computational requirements, compromising their efficacy. Modularisation techniques have been developed to address these issues by identifying and quantifying static and dynamic modules of the fault tree separately by using binary decision diagrams and Markov models. Although these approaches appear effective in reducing computational effort and avoiding state-space explosion, the reliance of the Markov chain on exponentially distributed data of system components can limit their widespread industrial applications. In this paper, we propose a hybrid modularisation scheme where independent sub-trees of a DFT are identified and quantified in a hierarchical order. A hybrid framework with the combination of algebraic solution, Petri Nets, and Monte Carlo simulation is used to increase the efficiency of the solution. The proposed approach uses the advantages of each existing approach in the right place (independent module). We have experimented the proposed approach on five independent hypothetical and industrial examples in which the experiments show the capabilities of the proposed approach facing repeated basic events and non-exponential failure distributions. The proposed approach could provide an approximate solution to DFTs without unacceptable loss of accuracy. Moreover, the use of modularised or hierarchical Petri nets makes this approach more generally applicable by allowing quantitative evaluation of DFTs with a wide range of failure rate distributions for basic events of the tree.

Highlights

Safety-critical systems are widely used in many industries
DYNAMIC FAULT TREE ANALYSIS The dynamic fault trees (DFTs) extends the capability of static fault trees (SFTs) by introducing dynamic gates like the Priority AND (PAND), Priority OR (POR), Functional dependency (FDEP), SPARE, and SEQ to model time-dependent failure behaviour of systems
In this paper, we have addressed the limitations of the existing modularisation techniques for DFT analysis by proposing a novel approach based on algebraic solutions and Petri nets (PN) to quantify dynamic fault trees

Summary

INTRODUCTION

Safety-critical systems are widely used in many industries. Reliability engineering concentrates on assuring safety and reliability of such systems by identifying potential risks that may be caused by their failure and thereby determining necessary actions to reduce the likelihood of these risks. A Weibull-distribution-based modularisation scheme was proposed in [43] where both analytical and simulation techniques were used to solve DFTs. Table 1 shows a comparison between different features of the existing modularisation-based DFT analysis approaches. As Markov chains are only applicable given an exponentially distributed failure rate, the use of Markov chains limits the application of these approaches to a particular class of DFTs. it is beneficial to utilise other DFT solution approaches in a modularisation scheme, which can alleviate the above limitation, making the scheme capable of solving more general types of DFTs. in most existing modularisation schemes, dynamic modules are not decomposed further even when they contain independent modules within them. The capabilities and accuracy of the proposed method are illustrated and compared through using different well-known hypothetical and industrial case studies facing issues such as repeated basic events and non-exponential failure distributions

DYNAMIC FAULT TREE ANALYSIS

NUMERICAL EXAMPLES AND EVALUATION

CONCLUSION