Combination of Component Fault Trees and Markov Chains to Analyze Complex, Software-Controlled Systems
Year: 2018
Type: conference-paper
Abstract: Fault Tree analysis is a widely used failure analysis methodology to assess a system in terms of safety or reliability in many industrial application domains. However, with Fault Tree methodology there is no possibility to express a temporal sequence of events or state-dependent behavior of software-controlled systems. In contrast to this, Markov Chains are a state-based analysis technique based on a stochastic model. But the use of Markov Chains for failure analysis of complex safety-critical systems is limited due to exponential explosion of the size of the model. In this paper, we present a concept to integrate Markov Chains in Component Fault Tree models. Based on a component concept for Markov Chains, which enables the association of Markov Chains to system development elements such as components, complex or software-controlled systems can be analyzed w.r.t. safety or reliability in a modular and compositional way. We illustrate this approach using a case study from the automotive domain.
Authors: Marc Zeller, Francesco Montrone
Institution: Siemens (Germany)
Language: English
Topic: Risk and Safety Analysis
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2937666361