Mathematical models have become essential in modern engineering to solve a variety of tasks, e. g. to guide and validate the design of technical systems, to engineer and test automation architectures, to determine performance, and to train system operators. A major obstacle in the application of model-based techniques in engineering tool chains is the incompatibility of the model formalisms that are employed by different tools and methodologies. Most modeling formalisms and model-based tools have been developed for a specific domain and possess specific strengths in this domain, and the transfer of models or the integration of different model components is a challenging task. The main contributions of this work are two novel methodologies for the algorithmic transformation of complex formalisms for discrete-continuous (hybrid) dynamic modeling and for the representation of industrial logic control systems. Based on comprehensive surveys and classifications of mathematical modeling formalisms for engineering applications, two different types of formalisms are identified, discrete-event-dominant modeling formalisms and equation-dominant modeling formalisms. The first transformation methodology enables the transformation of models from the discrete-event-dominant model exchange formalism Compositional Interchange Format (CIF) to the equation-dominant Modelica language while the second methodology allows the user to integrate logic control programs in the industry standard language Sequential Function Chart (SFC) with models of the controlled system. The transformations facilitate the execution of multi-formalism engineering tool chains, which is illustrated for a mixed continuous-batch chemical processing benchmark system and a two-tank system under logic control.
