Industrial IoT platforms face semantic interoperability challenges when integrating heterogeneous manufacturing equipment. While Asset Administration Shell (AAS), standardized by IEC 63278-1:2023, provides vendor-neutral digital representations, existing implementations lack automated reasoning capabilities. This work presents a semantic integration framework enhancing AAS with Knowledge Graph technologies through bidirectional transformation mechanisms. Developed within the PlatinA Industrial Internet of Things platform research (infrastructure designed for 50 concurrent devices, currently integrating 3 manufacturing systems), our hybrid architecture combines containerized AAS implementations with Apache Jena Fuseki RDF triple stores. We validate technical feasibility through proof-of-concept implementation using a precision milling system with real-time force monitoring, demonstrating successful AAS-to-RDF transformation preserving IEC 63278 compliance, sophisticated SPARQL-based queries for force deviation detection and equipment capability discovery, and practical integration with existing infrastructure. A three-layer manufacturing ontology enables automated reasoning through SWRL rules for equipment selection, maintenance prediction, and quality assessment. This proof-of-concept establishes the foundation for addressing critical manufacturing challenges including measurement validation (targeting reduction from 80% redundancy to 5-6%) and process anomaly detection (projected 89% automation rate), enabling intelligent resource allocation and cross-system interoperability through knowledge-driven decision making.
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