Semantic design and integration of simulation models in the industrial automation area

Simulations are software tools approximating and predicting the behavior of real industrial plants. Unlike real plants, the utilization of simulations cannot cause damages and it saves time and costs during series of experiments. A shortcoming of current simulation models is the complicated runtime integration into legacy industrial systems and platforms, as well as ad-hoc design phase, introducing manual and error-prone work. This paper contributes to improve the efficiency of simulation model design and integration. It utilizes a semantic knowledge base, implemented by ontologies and their mappings. The integration uses the Automation Service Bus and the paper explains how to configure the runtime integration level semantically. The main contributions are the concept of semantic configuration of the service bus and the workflows of simulation design and integration.