Leveraging ontologies and Asset Administration Shells for decision-support: A case study on production planning within the injection molding domain

A fundamental aspect of Industry 4.0 is interoperable asset-to-asset communication, essential for creating cross-company “lab of labs”. Such collaboration enables seamless data exchange across companies, streamlining manual processes like evaluating the capability of assets for specific manufacturing processes. While foundational technologies for asset interoperability exist, their integration and application in industrial contexts remain limited. Our research explores the integration of ontologies, which structure domain knowledge, and Asset Administration Shells (AAS), which represent assets in a standardized manner, to facilitate industrial interoperability. We have developed an architecture using an ontology-based graph database populated with AAS data, allowing automatic linking of AAS instances to corresponding class nodes. To demonstrate practical value, we have implemented this architecture using standardized software and tools, applying it to assess technical capabilities for a customer request in injection molding. Results confirm the potential for asset-to-asset communication in industry via graph databases, with benefits in flexible and scalable data management. However, limitations include unaddressed data safety and security concerns, as well as the need for updated database entries when AAS instances change. Additionally, challenges in scaling to integrate other domain ontologies should be tackled in future research. This work lays a foundation for advancing interoperable, cross-company data-sharing ecosystems.