Compiling Dyanamic Fault Trees into Dynamic Bayesian Nets for Reliability Analysis: The RADYBAN Tool

Abstract

In this paper, we present RADYBAN (Reliability Analysis with DYnamic BAyesian Networks), a software tool which allows to analyze systems modeled by means of Dynamic Fault Trees (DFT), by relying on automatic conversion into Dynamic Bayesian Networks (DBN). The tools aims at providing a familiar interface to reliability engineers, by allowing them to model the system to be analyzed with quite a standard formalism (i.e. DFT) based on specific extensions to the well-known methodology of Fault Trees; however, the tool also implements a modular algorithm for automatically translating a DFT into the corresponding DBN, without any explicit intervention from the end user. In fact, when the computation of specific reliability measures is requested, the tool exploits classical algorithms for the inference on Dynamic Bayesian Networks, in order to compute the requested parameters. This is performed in a totally transparent way to the user, who could in principle be completely unaware of the underlying Bayesian Network. However, the use of DBNs allows the tool to be able to compute measures that are not directly computable from DFTs, but that are naturally obtainable from DBN inference. After having described the basic features of the tool, we show how it operates on a real world example and we compare the unreliability results it generates with those returned by other methodologies, in order to verify the correctness and the consistency of the results obtained.