Fault trees analysis is essential to keep e.g. our power plants, trains, drones, medical devices, satellites and self-driving cars safe and operational. FTA usage is required by e.g. the Federal Aviation Authority (FAA), the Nuclear Regulatory Commission (NRC), in ISO 26262 for autonomous driving or for software development in aerospace systems (by NASA and ESA). Various fault tree extensions exist that increase expressiveness while yielding succinct and comprehensible models e.g. dynamic fault trees, their analysis is however a main bottleneck: techniques do not scale and require substantial manual effort.
In collaboration with Twente and RWTH Aachen universities, we developed a fully automatic, scalable, and state-of-the-art tool for the analysis of dynamic fault trees. It goes beyond the capabilities of existing commercial tools for fault tree analysis in offering more flexible modelling and analyses.
Because of limited expressiveness, SFTs cannot model dynamic behaviour of systems in which:
ISO 26262:2011 demands rigorous risk assessments in automotive industry:
Rapidly increased usage of AI components in modern systems necessitates a rigorous risk assessment
FTA focuses on computing various dependability metrics, i.e. key performance
indicators that measure how well a system performs. Standard metrics are the
Reliability : the probability that no failure occurred until time T
Conditional Reliability : the probability that no failure occurred until time T given a component has already failed
Availability : the average percentage of time that a system is operational
Mean Time to Failure (MTTF): the mean time between failures,
Criticality of components : to what extent does a component failure contribute to a system failure, etc.
Our tools also handles various extensions that include the cost and impact of failures.