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IDENTIFYING SUCCESSFUL APPROACHES DURING TESTING ACTIVITIES IN ENGINEERING DESIGN

Published online by Cambridge University Press:  19 June 2023

Oliver Liewerenz ,
Patric Grauberger ,
Thomas Nelius  and
Sven Matthiesen
Oliver Liewerenz*
Affiliation:
Karlsruhe Institute of Technology
Patric Grauberger
Affiliation:
Karlsruhe Institute of Technology
Thomas Nelius
Affiliation:
Karlsruhe Institute of Technology
Sven Matthiesen
Affiliation:
Karlsruhe Institute of Technology
*
Liewerenz, Oliver, Karlsruhe Institute of Technology, Germany, [email protected]

Abstract

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Testing activities to gain specific design knowledge play an essential role in engineering design, when a structure needs to be developed, for which knowledge from analytical models or documentation is missing. As research into these testing activities is difficult, few insights into successful approaches exist.

In this contribution, we investigate testing activities to gain specific design knowledge through a laboratory task, where 10 engineering students optimize a system using a web-based process chain including rapid prototyping and testing. Design and testing data are acquired from 110 prototypes in 3 hours. A differentiation of performance is conducted and approaches of high- and low-performers are investigated to identify patterns.

Based on these patterns, hypotheses, and metrics indicating successful and non-successful approaches are derived as basis for development of metrics for testing to gain specific design knowledge. A successful approach was overstep the limit, where participants accept destruction of their system to identify boundaries. An unsuccessful approach was the change of many parameters in later tests. These hypotheses and their metrics can then be used in development and validation of support for testing.

Keywords

Data-driven engineering designTesting activitiesDesign methodsEmbodiment designProcess modelling
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 2205 - 2214
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), 2023. Published by Cambridge University Press

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