Toward a Mapping of Capability and Skill Models using Asset Administration Shells and Ontologies

TL;DR

This paper tackles the interoperability gap between two modeling paradigms for production capabilities and skills: ontological representations and Asset Administration Shell submodels. It analyzes the similarities and gaps between CaSkMan ontology and AAS-based models, and then proposes a bidirectional mapping framework using RML for AAS-to-ontology transformations and RDFex for the reverse. The key contribution is a concrete mapping concept with initial rules and an evaluation plan, highlighting practical steps toward interoperable equipment descriptions in Industry 4.0. The work enables switching between model types to leverage the tooling and planning capabilities of each approach, potentially improving plug-and-produce deployments and maintenance scenarios.

Abstract

In order to react efficiently to changes in production, resources and their functions must be integrated into plants in accordance with the plug and produce principle. In this context, research on so-called capabilities and skills has shown promise. However, there are currently two incompatible approaches to modeling capabilities and skills. On the one hand, formal descriptions using ontologies have been developed. On the other hand, there are efforts to standardize submodels of the Asset Administration Shell (AAS) for this purpose. In this paper, we present ongoing research to connect these two incompatible modeling approaches. Both models are analyzed to identify comparable as well as dissimilar model elements. Subsequently, we present a concept for a bidirectional mapping between AAS submodels and a capability and skill ontology. For this purpose, two unidirectional, declarative mappings are applied that implement transformations from one modeling approach to the other - and vice versa.