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Data-Driven Design Support for Additively Manufactured Heating Elements

Published online by Cambridge University Press:  26 May 2022

K. Hilbig ,
M. Nowka ,
J. Redeker ,
H. Watschke ,
V. Friesen ,
A. Duden  and
T. Vietor
K. Hilbig*
Affiliation:
Technische Universität Braunschweig, Germany
M. Nowka
Affiliation:
Technische Universität Braunschweig, Germany
J. Redeker
Affiliation:
Technische Universität Braunschweig, Germany
H. Watschke
Affiliation:
Technische Universität Braunschweig, Germany
V. Friesen
Affiliation:
Technische Universität Braunschweig, Germany
A. Duden
Affiliation:
Technische Universität Braunschweig, Germany
T. Vietor
Affiliation:
Technische Universität Braunschweig, Germany
*
k.hilbig@tu-braunschweig.de

Abstract

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Additive Manufacturing (AM) enables innovative product designs. One promising research field is AM of integrated electrically structures, e.g. heating panels using Joule effect. A mayor challenge in designing heating panels using AM is the dependency of its resultant resistivity from material, process and geometry parameters. The goal-oriented design of heating panels with individual surface temperatures the interactions between these parameters need to be understand. Therefore, a data-driven design approach is developed that facilitates a design of heating panels with specific properties.

Keywords

data-driven designdesign support systemadditive manufacturingelectrically conductive polymersheat-generating structures
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 1391 - 1400
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), 2022.

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