Building a Knowledge Graph with Inference for a Production Machine Using the Web of Things Standard

This paper presents an architecture for a knowledge-based system (KBS) that consists of a Knowledge Graph, an inference engine and services. The Web of Things standard is used to translate sensor data from a production machine into an RDF graph. The KBS architecture is implemented for a physical twin of a real machine using open-source Semantic Web technologies. The performance evaluation of the system reveals limitations for the application in production.