Hybrid modeling approaches with a view to model output prediction for industrial applications

The combination of different modeling approaches has been applied to create so-called Grey-Box-Models for a few decades. But due to increasing data availability provided by IoT-devices, new possibilities regarding data-driven modeling arise. The purpose of this article is to develop a concept which is able to combine data-driven models created during operation with such respective theoretical models created during the design phase. The model combination should result in an added value for the operator at shop floor in the shape of real-time-capable simulation models. Initially, the different modeling methods as well as the way they can be combined are introduced. Afterwards, a concept for training and operation will be presented. The article ends with a first example demonstrating the potential of the approach.