MDAE

Model-Driven Automation Engineering (MDAE)

Within a complex process such like Automation projects many different disciplines are involved. Additionally, each discipline has its own data, information and models to shape the result.

Exemplary, to electrical engineers are interested to find the best setting for terminals within a electrical control cabinet, whilst mechanical engineers define the architecture of the plant. This process has to be done in parallel and with respect to each other. This becomes obvious when we think of mechanical engineers inserting a new control module into the cabinet, which results in the need for at least one more terminal.

Within each domain exists models and tools which work (almost) perfectly within their scope. Besides this exists a wish for more data exchange possibility between tools of different domains. Reconsidering our example from above, this would mean, that the electrical engineer gets at least a message which tells him his plans have to be updated since a module was placed.
We are researching new approaches in order to come up with an idea to solve this problem. A first step is to abstract from current tools and data onwards to meta-models. The next step is probably the transformation of knowledge from one domain into the other. This may be done via Triple Graph Grammars (TGGs). As a result we are looking forward to workflows, that may  identify inconsistencies and problems in two different models automatically.

Project Partners

Our research is supported mainly by the Siemens AG, which provides us any domain-specific knowledge and helps us to develop use cases that arise from typical engineering tasks. Our common goal is to identify strengths and potentials of our approach, as well as problems and restrictions.http://www.siemens.de

Additionally this research takes place within the Graduate School Computational Engineering at TU Darmstadt, which provided Marius Lauder a scholarship.

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