Combining various solution techniques for dynamic fault tree analysis of computer systems (original) (raw)
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Dynamic Fault Tree Analysis: State-of-the-Art in Modeling, Analysis, and Tools
2020
YesSafety and reliability are two important aspects of dependability that are needed to be rigorously evaluated throughout the development life-cycle of a system. Over the years, several methodologies have been developed for the analysis of failure behavior of systems. Fault tree analysis (FTA) is one of the well-established and widely used methods for safety and reliability engineering of systems. Fault tree, in its classical static form, is inadequate for modeling dynamic interactions between components and is unable to include temporal and statistical dependencies in the model. Several attempts have been made to alleviate the aforementioned limitations of static fault trees (SFT). Dynamic fault trees (DFT) were introduced to enhance the modeling power of its static counterpart. In DFT, the expressiveness of fault tree was improved by introducing new dynamic gates. While the introduction of the dynamic gates helps to overcome many limitations of SFT and allows to analyze a wide ra...
Computerized fault tree construction for improved reliability analysis
Risk Analysis VII, 2010
Fault Tree Analysis is a well-known method for reliability evaluation of systems. However, manual construction of fault trees is a tedious and time-consuming task. Thus, many researchers tried to get benefit of high speed and accuracy of digital computers to automate this process. Automated construction of fault trees can be very useful in system reliability analysis, especially in design step, where we need to choose the most reliable design out of several design options.
A Hybrid Modular Approach for Dynamic Fault Tree Analysis
IEEE Access
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. INDEX TERMS Reliability analysis, fault tree analysis, dynamic fault trees, modularisation, petri nets.
Added value in fault tree analyses
2000
It is recognized that the usual output of a fault tree analysis in some studies is not sufficiently informative. For added value in a widely used instrument for doing risk analyses, a Markovian approach is suggested. It is shown how to extend the calculations of the standard fault tree gates, so that information is available not only on the failure
2008
In this paper, we present Radyban (Reliability Analysis with DYnamic BAyesian Networks), a software tool which allows to analyze a dynamic fault tree relying on its conversion into a dynamic Bayesian network. The tool implements a modular algorithm for automatically translating a dynamic fault tree into the corresponding dynamic Bayesian network and exploits classical algorithms for the inference on dynamic Bayesian networks, in order to compute reliability measures.
Including Systematic Faults into Fault Tree Analysis
Fault Detection, Supervision and Safety of Technical Processes 2006, 2007
Fault Tree Analysis (FTA) is a technique widely used for fault forecasting of physical systems. Although FTA is considered a well established safety analysis technique, paradoxically classical Fault Trees include only random faults. However, in modern automated systems, undesirable events arise not only from random hardware faults but also from defects in the logic of software controllers that control the physical system. Faults generated by these software controllers are systematic faults caused by coding errors or misinterpretations of control requirements. This paper proposes an extension to the basic Fault Trees construction process which takes into account this category of faults and advocates the use of dynamic and temporal gates to model it.
Fault Trees, Decision Trees, And Binary Decision Diagrams: A Systematic Comparison
Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021), 2021
In reliability engineering, we need to understand system dependencies, cause-effect relations, identify critical components, and analyze how they trigger failures. Three prominent graph models commonly used for these purposes are fault trees (FTs), decision trees (DTs), and binary decision diagrams (BDDs). These models are popular because they are easy to interpret, serve as a communication tool between stakeholders of various backgrounds, and support decision-making processes. Moreover, these models help to understand real-world problems by computing reliability metrics, minimum cut sets, logic rules, and displaying dependencies. Nevertheless, it is unclear how these graph models compare. Thus, the goal of this paper is to understand the similarities and differences through a systematic comparison based on their (i) purpose and application, (ii) structural representation, (iii) analysis methods, (iv) construction, and (v) benefits & limitations. Furthermore, we use a running example based on a Container Seal Design to showcase the models in practice. Our results show that, given that FTs, DTs and BDDs have different purposes and application domains, they adopt different structural representations and analysis methodologies that entail a variety of benefits and limitations, the latter can be addressed via conversion methods or extensions. Specific remarks are that BDDs can be considered as a compact representation of binary DTs, since the former allow sub-node sharing, which makes BDDs more efficient at representing logical rules than binary DTs. It is possible to obtain cut sets from BDDs and DTs and construct a FT using the (con/dis)junctive normal form, although this may result in a sub-optimal FT structure.