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METHOD FOR IDENTIFYING SUITABLE COMPONENTS FOR FUNCTIONAL INTEGRATION – FOCUSING ON GEOMETRIC CHARACTERISTICS

Published online by Cambridge University Press:  27 July 2021

Michael P. Voigt*
Affiliation:
University of Stuttgart
Dominik Klaiber
Affiliation:
Braunschweig University of Technology
Patrick Hommel
Affiliation:
University of Stuttgart
Daniel Roth
Affiliation:
University of Stuttgart
Hansgeorg Binz
Affiliation:
University of Stuttgart
Thomas Vietor
Affiliation:
Braunschweig University of Technology
*
Voigt, Michael P., University of Stuttgart, Institute for Engineering Design and Industrial Design, Germany, michael.voigt@iktd.uni-stuttgart.de

Abstract

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The approach of functional integration has the potential to solve challenges regarding lightweight design and resource efficiency since the number of parts and therefore the weight and needed installation space can be reduced. One important step in developing integrative concepts is the pre-selection of suitable functions or components. Previous methods of pre-selection take various aspects into account. However, pre-selection based on these methods usually requires additional tables and forms, whose preparation and editing quickly becomes time-consuming. At the same time, most of the development engineers are working on CAD models. However, their use in the selection of suitable integration partners is not yet supported sufficiently. The development of more than 80 concepts on five different vehicles has shown that the consideration of geometric properties (position, orientation, size) is effective, as they can be identified with minimal analysis effort while working on CAD. In this paper a four-step procedure is presented how integration partners can be identified directly on the basis of CAD models. A following evaluation with development engineers in practice completes the research.

Information

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), 2021. Published by Cambridge University Press