Publikation
Queryable AAS Graphs for AI Agents: An Event-Driven Knowledge Graph Integration for AAS Environments
Gerhard Sonnenberg; Peter Stein; Fabio Espinosa; Daniel Porta
In: IEEE International Conference on Emerging Technologies and Factory Automation. IEEE International Conference on Emerging Technologies and Factory Automation (ETFA-2025), IEEE, 2025.
Zusammenfassung
The Asset Administration Shell (AAS) plays a key role in Industry 4.0, providing a standardized digital representation of industrial assets to enable interoperability and data exchange.
However, information retrieval with complex queries is still in its infancy despite recent advances in the specification of a dedicated query language, which will be hard to implement for different SDKs and storage back-ends.
This paper proposes an event-driven architecture that integrates AAS contents into a Neo4j-based knowledge graph using Apache Kafka. This enables powerful, relationship-oriented Cypher queries for complex information retrieval and supports advanced cross-validation of references. The knowledge graph will be kept in sync with changes in the AAS. This establishes a solid foundation for advanced natural language user interfaces. As a proof-of-concept, we implemented an AI agent using a Large Language Model (LLM) and a standardized Neo4j tool integration by means of the Model Context Protocol (MCP) for question answering.
Thus, the paper contributes to making the AAS more accessible and actionable for AI-driven industrial applications in a broad range of use cases without the need for a dedicated query language. The source code is publicly available on GitHub.