For many practical applications, a combination of theoretical and experimental modelling appears feasible. Qualitative knowledge about the most significant effects are often known or easily accessible. This contribution suggests a semi-physical modelling approach based on the special architecture of local models. Due to their inherent transparency, these models are very well suited for the incorporation of mainly qualitative process knowledge. The integration of prior knowledge is realised by an adaptation of the model structure to that one of the process. As a result, the final process-specific models are characterised by high generalisation performance also in situations with only few measurement data.