Fault tree analysis

TLDR: Fault tree analysis (FTA) is a very prominent method to analyze the risks related to safety and economically critical assets, like power plants, airplanes, data centers and web shops as mentioned in this paper.

About: This article is published in Computer Science Review.The article was published on 2015-02-01 and is currently open access. It has received 504 citations till now. The article focuses on the topics: Fault tree analysis.

Figures

Figure 7: Example FT showing the propagation of failure probability in a single-time FT.

Table 6: Overview of DFT qualitative analysis methods

Figure 14: Example conversion of DFT to a Continuous Time Markov Chain. States corresponding to system failures (goal states) are indicated by a double circle. Transition fi denotes the failure of BE Ei, and occurs with rate λi.

Figure 20: State-event fault tree example of two computer processes P1 and P2, which fail approximately once every 10 hours. The watchdog process W restarts any failed process once per hour. System failure occurs when both P1 and P2 are down.

Figure 4: Example conversion of SFT to BDD

Table 2: Applicability of stochastic measures to different FT types

Frequently asked questions

Q1. What contributions have the authors mentioned in the paper "Fault tree analysis: a survey of the state-of-the-art in modeling, analysis and tools" ?

This paper surveys over 150 papers on fault tree analysis, providing an in-depth overview of the state-of-the-art in FTA. Concretely, the authors review standard fault trees, as well as extensions such as dynamic FT, repairable FT, and extended FT. For these models, the authors review both qualitative analysis methods, like cut sets and common cause failures, and quantitative techniques, including a wide variety of stochastic methods to compute failure probabilities. 

Q2. What are the future works mentioned in the paper "Fault tree analysis: a survey of the state-of-the-art in modeling, analysis and tools" ?

This overview lead to several observations and directions for future research. Thus, the authors suggest extensive field studies here.