Ontology-driven Integration of System-Theoretic Process Analysis and Model-Based Safety Analysis for Comprehensive Safety Assessment

This work aims to improve safety assessments in complex systems by presenting an ontology-driven approach to integrating Model-Based Safety Analysis (MBSA) and System-Theoretic Process Analysis (STPA).The ontology serves as an interface with two main goals: (1) to filter STPA scenarios and identify failure-based cases for MBSA, and (2) to automatically translate the filtered scenarios into MBSA-compatible feared events (i.e., "observers").By bridging STPA's hazard identification methodology with MBSA's failure-based analysis, this approach offers a more efficient and comprehensive framework for system safety and reliability assessment.Even though the improvement of overall safety is a goal shared by both STPA and MBSA, their approach to doing so is different.STPA provides a broad hazard identification framework capturing a range of scenario types, including non-failure cases driven by systemic, human, and organizational factors.In contrast, MBSA focuses on the study of failure propagations.These methodologies are thus complementary and can offer a more complete picture when used together; however, achieving such integration requires a systematic approach to filter and map relevant information between them.To categorize STPA scenarios and eliminate those unsuitable for MBSA, the created ontology serves as a common framework by ensuring that only scenarios appropriate for MBSA's failure-based approach are transferred.The ontology lessens the need for human intervention improving accuracy and enabling more thorough fault propagation analyses by automatically converting compatible STPA scenarios into MBSA's format.Early findings show that this strategy improves the effectiveness of the safety assessment process while also streamlining the integration of STPA and MBSA.The ontology-driven interface enables the utilization of both methodologies' strengths through a methodical and structured mapping, providing a unified framework that can be tailored to the intricacies of contemporary safety-critical systems.