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CONNECTING DESIGN ITERATIONS TO PERFORMANCE IN ENGINEERING DESIGN

Published online by Cambridge University Press:  19 June 2023

Ademir-Paolo Vrolijk ,
Yuanzhe Deng  and
Alison Olechowski
Ademir-Paolo Vrolijk*
Affiliation:
University of Toronto
Yuanzhe Deng
Affiliation:
University of Toronto
Alison Olechowski
Affiliation:
University of Toronto
*
Vrolijk, Ademir-Paolo University of Toronto, Canada, [email protected]

Abstract

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No matter a system's size, complexity, or domain, iterations are fundamental to its design process. However, there is a duality: iterations are both signs of usefully exploring the system's design space and failure to find an appropriate solution. This ambiguity means that we have not been able to connect teams’ iterating behavior to their design's performance, potentially obscuring a way to influence the design process.

As such, our exploratory study unpacks the relationship between design iterations and performance. We observed 88 teams in the 2020 Robots to the Rescue Competition in rich detail. Using logs of 7,956 iterations on a Computer-Aided Design platform, we analyzed how high- and low-performing teams revised their submissions, searching for consistent differences in their behavior. We found significant differences in the iterations’ number, scale, and cadence between these groups of teams. These findings emphasized the correlation between certain iteration patterns and the success of a design: the best teams will likely revise differently than the worst ones. It also showed the importance of a fine-grained, time- dependent view of the design process to resolve open questions in the literature.

Keywords

Design processDesign RevisionConceptual designComputer Aided Design (CAD)Multi-user CAD
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 1067 - 1076
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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