Talks and Poster Presentations (with Proceedings-Entry):

F. Rinker, L. Waltersdorfer, M. Schüller, D. Winkler:
"Graph-based Model Inspection Tool for Multi-Disciplinary Production Systems Engineering";
Talk: Modelswards 2020, Valetta, Malta; 2020-02-25 - 2020-02-27; in: "Modelswards 2020", ScitePress, (2020), ISBN: 978-989-758-400-8; 116 - 125.

English abstract:
Background. In Production Systems Engineering (PSE), the planning of production systems involves domain
experts from various domains, such as mechanical, electrical and software engineering collaborating and modeling their specific views on the system. These models, describing entire plants, can reach a large size (up to
several GBs) with complex relationships and dependencies. Due to the size, ambiguous semantics and diverging views, consistency of data and the awareness of changes are challenging to track. Aim. In this paper we
explore visualizations mechanisms for a model inspection tool to support consistency checking and the awareness of changes in multi-disciplinary PSE environments, as well has more efficient handing of AutomationML
(AML) files. Method. We explore various visualization capabilities that are suitable for hierarchical structures
common in PSE and identified requirements for a model-inspection tool for PSE purposes based on workshops with our company partner. A proof-of concept software prototype is developed based on the elicited
requirements. Results. We evaluate the effectiveness of our Information Visualisation (InfoVis) approach in
comparison to a standard modeling tool in PSE, the AutomationML Editor. The evaluation showed promising
results for handling large-scale engineering models based on AML for the selected scenarios, but also areas
for future improvement, such as more advanced capabilities. Conclusion. Although InfoVis was found useful
in the evaluation context, in-depth analysis with domain experts from industry regarding usability and features
remain for future work.

domain-specific modeling, production systems engineering, model-driven engineering, domain-specific languages, model quality, multi-disciplinary engineering.

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Created from the Publication Database of the Vienna University of Technology.