The digitalization of industrial production systems, commonly referred to as Industry 4.0 (I4.0), has revolutionized manufacturing by integrating connected technologies with intelligent automation. However, this transformation has also increased system complexity and expanded the attack surface of operational technology (OT) environments. Traditional risk assessment models often struggle to accurately represent the dynamic interactions and dependencies within these systems, as operational changes, software updates, and the integration of new devices continuously reshape the security landscape. Security breaches pose significant risks to industrial facilities and the environment, making it essential to consider safety and security aspects throughout the entire system lifecycle.

This project comprises a model-based evaluation methodology aimed at bridging the gap between manual and automated safety and security requirements in Industry 4.0 OT environments. The approachincludes the development of a metamodel that captures OT infrastructure components and their relationships. This model is subsequently implemented as a graphical user interface (GUI) enabling key functionalities such as network scanning, application and interface identification, and AI-supported data acquisition. Risk assessment and compliance evaluation are conducted based on industry standards such as IEC 62443-3-3 and IEC 61508, as well as methods including LOPA, SEFR (HAZID), STRIDE, and DREAD. The extracted data are then transformed into structured system models (e.g., OWL, AutomationML) to enable visualization and analysis