Ontology-Driven Modeling and Integration of Production Processes in Advanced Driver-Assistance Systems within the Gaia-X Ecosystem

Integrating semantic technologies, particularly ontologies, into production processes represents a significant advancement in achieving interoperability and efficiency in modern manufacturing. This paper systematically models production processes through ontologies tailored for assistive and autonomous driving systems. The focus lies on capturing critical parameters and process steps, structuring them into machine-readable formats to facilitate semantic interoperability and enhance process traceability.The ontology development was conducted using the Web Ontology Language (OWL) and the Protégé tool, supported by Shape Constraint Language (SHACL) for validation and JSON-LD for data serialization. The ontologies were designed to be flexible and modular, enabling their applicability beyond the modeled processes while adhering to Gaia-X guidelines for data ecosystems. The successful integration into the Gaia-X platform was achieved by creating compliant ontology files, rigorous validation, and a structured deployment process. This demonstrates a replicable framework for the semantic representation and sharing of production knowledge within collaborative environments.The results highlight the potential of ontologies for enhancing manufacturing processes and provide a foundation for their broader application in intelligent production systems. This work contributes to the growing body of research on semantic technologies in manufacturing, offering insights into scalable, standardized, and interoperable solutions for Industry 4.0 and beyond.