IMPROVING SAFETY BY INTEGRATING DYSFUNCTIONAL ANALYSIS INTO THE DESIGN OF RAILWAY SYSTEMS
Free (open access)
399 - 411
SANA DEBBECH, PHILIPPE BON, SIMON COLLART-DUTILLEUL
In order to cope with the increasing design complexity of safety-critical systems, safety assurance should be considered as early as possible in the design process. Using Model-Based System Engineering (MBSE) approaches however lead to new challenges regarding the cohesive integration of both safety engineering and system design along the system development process. Moreover, it helps to anticipate safety problems and detect errors as soon as possible. This is the case of railway systems, which are complex socio-technical systems. From this point of view, the purpose of the present study is to formalize a safety reasoning based on the definition of critical scenarios. The objective is to propose a proactive approach that takes these requirements into account early in the system architecture design. By identifying the impact on the design of the architecture, we will ensure safety by integrating technical devices and human interventions. Based on the related literature, the Preliminary Risk Analysis (PRA) is attested to define safety conditions. These safety requirements are expressed with a high level of abstraction according to the level of knowledge engineering. Qualitative risk analysis methods, such as Fault Tree Analysis (FTA) will be used to analyze the propagation of failures. The second challenge is to trace the high level requirements during the design steps. In order to help the designer to consider safety aspect in the system architecture synthesis, we integrate safety concerns from early design stages, within the MBSE approach. In this paper, we propose a methodology to effectively identify safety conditions, thus to anticipate risks. We also focus our work on the European Railway Traffic Management System (ERTMS). Finally, we applied specific transformation rules on our ERTMS ontology in order to build a Unified Modeling Language (UML) model.
dysfunctional analysis, safety requirements, model-based safety engineering, ontology, ERTMS