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Holistic Digital Function Modelling with Graph-Based Design Languages

Published online by Cambridge University Press:  26 July 2019

Michael Elwert
Affiliation:
University of Applied Sciences Ravensburg-Weingarten;
Manuel Ramsaier
Affiliation:
University of Applied Sciences Ravensburg-Weingarten;
Boris Eisenbart
Affiliation:
Swinburne University of Technology
Ralf Stetter*
Affiliation:
University of Applied Sciences Ravensburg-Weingarten;
*
Contact: Stetter, Ralf, University of Applied Sciences Ravensburg-Weingarten, Mechanical Engineering, Germany, ralf.stetter@hs-weingarten.de

Abstract

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Graph-based design languages offer a promising approach to address several major issues in engineering, e. g. the laborious manual transfer between CAD and CAE. Such languages generate a digital meta- or system model storing all relevant information about a design and feed this into any relevant CAE tool as needed to simulate and test the impact of any design variation on the resulting product performance. As this can be automated in digital compilers to perform systematic design variation for an almost infinite amount of parameters, such graph-based languages are a powerful means to generate viable design alternatives and thus permit fast evaluations.

To leverage the full potential of graph-based design languages, possibilities are presented to expand their applicability into the domain of product functions. This possibilities allow to cohesively link integrative function modelling to product structures. This intends to close the gap between the early, abstract stages and the systematic, concrete design generation and validation with relevant CAE tools. In this paper, the IFM Framework was selected as integrated function model to be linked with the graph- based design languages.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

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