Quantitative Safety Analysis for Industry
A Model-Based Approach
Time: Mon 2026-06-15 13.00
Location: Q2, Malvinas väg 10, Stockholm
Language: English
Subject area: Machine Design
Doctoral student: Stefan Kaalen , Mekatronik och inbyggda styrsystem, TRATON
Opponent: Professor Martin Fränzle, Carl von Ossietzky Universität Oldenburg, Department of Computing Science Research Group Foundations and Applications of Systems of Cyber-Physical Systems
Supervisor: Mattias Nyberg, Mekatronik och inbyggda styrsystem, TRATON; Martin Törngren, Mekatronik och inbyggda styrsystem
Abstract
Within the industry, quantitative safety analysis is often based on well-established methods that have existed for decades. The perhaps most prominent example is fault trees, in which the probability of a system failure is computed from the probability of component-level malfunctions. While these classical methods has the advantage of being well-established and easy to understand, they are lacking in two major areas. Firstly, the models does not describe the architecture of the system. Since this is the case, they are error-prone when changes are made in the system and two different engineers tend to produce vastly different models of the system. Secondly, they only support exponential distributions as a mean to introduce stochastic behavior in the models. As a result of this restriction, the complex dynamic behavior of the cyber-physical system that constitutes a road vehicle today cannot be modeled accurately. Within the academia, many methods, languages, and tools have been suggested in the last decades that would would help circumvent one or both of these restrictions. However, these methods has to date not reached prominent traction within the industry. In this thesis, languages and analysis methods with tool support for quantitative safety analysis that surpass the above mentioned restrictions while still being attractive candidates for the industry are presented.