Abstract
In this paper a new modeling framework for the dependability analysis of complex systems is presented and related to dynamic fault trees (DFTs). The methodology is based on a modular approach: two separate models are used to handle, the fault logic and the stochastic dependencies of the system. Thus, the fault schema, free of any dependency logic, can be easily evaluated, while the dependency schema allows the modeler to design new kind of non-trivial dependencies not easily caught by the traditional holistic methodologies. Moreover, the use of a dependency schema allows building a pure behavioral model that can be used for various kinds of dependability studies. In the paper is shown how to build and integrate the two modular models and convert them in a Stochastic Activity Network. Furthermore, based on the construction of the schema that embeds the stochastic dependencies, the procedure to convert DFTs into static fault trees is shown, allowing the resolution of DFTs in a very efficient way.
Highlights
Nowadays, technology and technological systems are fundamental constituents of any industrial process
In this paper is presented an application of this modeling framework and a practical case study to convert dynamic fault trees (DFTs) will be shown: the stochastic dependencies of the DFT will be captured by the Dependency Graph (DG) model, while the system fault logic will be described by a static Fault Tree (FT)
In the following this modular model is referred as a Stochastic Dependency Graph Fault Tree (DGFT)
Summary
Technology and technological systems are fundamental constituents of any industrial process In such a context, the demand of more effective and precise risk assessments and performability evaluations has highlighted the necessity of adequate, specific dependability evaluation techniques and methods. Dynamic Fault Tree (DFT) [1,2] stands out for its characteristics including: a valid formalism, a high level language of description and several resolution algorithms For these reasons DFT has became a benchmark for many other modeling framework for the dependability. In this paper is presented an application of this modeling framework and a practical case study to convert DFT will be shown: the stochastic dependencies of the DFT will be captured by the DG model, while the system fault logic will be described by a static Fault Tree (FT). In the following this modular model is referred as a Stochastic Dependency Graph Fault Tree (DGFT)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
