A Method to Automatically Generate Semantic Skill Models from PLC Code - Kocher, Aljosha; Jeleniewski, Tom; Fay, Alexander (IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society, 2021)
The use of ontologies for models of machines and their capabilities and skills provides advantages for manufacturers that want to quickly adapt to changing customer requirements or fluctuating demands. Unfortunately, creating such models requires a high level of expertise in semantic technologies. In typical automation engineering workflows, there is neither the personnel nor the time to create such models manually.In this contribution, we describe an approach to automatically create skill models from IEC 61131-3 code. This approach consists of a dedicated PLC programming library and an automatic transformation of PLC code to a skill ontology. After implementing a skill as a PLC program using the presented library, this program can be exported as PLCopen XML which in turn is automatically transformed into an ontology. Additional efforts for PLC developers are thereby kept at a minimum. The presented approach has been evaluated using a modular laboratory plant. For two different modules, skills were implemented on separate PLCs. After transforming these skills to our skill ontology, this ontology was used to register the skills at a skill-based control platform. Using this platform, the skills were used together in order to perform one section of a production process.