Integrating heterogeneous engineering knowledge and tools for efficient industrial simulation model support

Abstract

Design of simulation models and their integration into industrial automation systems require knowledge from several heterogeneous data sources and tools. Due to the heterogeneity of engineering data, the integration of the tools and data are time-consuming and error-prone tasks nowadays. The key goal of this article is to provide an effective and efficient integration of heterogeneous data sources and tools as a knowledge basis to support dynamic simulation for industrial plants. The integrated knowledge is utilized both (i) in the design phase of simulation models for defining structure and interfaces of the models and (ii) in the runtime phase of industrial systems for model-driven configuration of the integrated environment. Reaching such goals with a manual approach or point-to-point integration is not beneficial as it may be possible for a few tools and data sources, but quickly gets very complex. A growing number of elements increases the risk of errors and the effort needed for integration. The proposed solution is based on a specification of a common data model to represent engineering knowledge and a service-oriented tool integration with the Engineering Service Bus. Engineering knowledge is integrated in a knowledge base implemented with ontologies in Web Ontology Language-Description Logic (OWL-DL). The proposed approach is demonstrated and evaluated on an educational hydraulic system. Major results of the article are: (i) a data model to represent engineering knowledge for dynamic industrial systems, (ii) the integration platform that, based on this model, integrates the tools for system design and runtime, and (iii) basic design-time and runtime processes for the integrated industrial simulations.