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THE INFLUENCE OF REPRESENTATION ON SYSTEM INTERPRETATION: A SEARCH FOR MOST COMMON SET PARTITIONS

Published online by Cambridge University Press:  19 June 2023

Alexander R. Murphy ,
Apurva R. Patel ,
Stefan Zorn ,
Kilian Gericke  and
Joshua D. Summers
Alexander R. Murphy*
Affiliation:
University of Texas at Dallas;
Apurva R. Patel
Affiliation:
University of Texas at Dallas;
Stefan Zorn
Affiliation:
University of Rostock
Kilian Gericke
Affiliation:
University of Rostock
Joshua D. Summers
Affiliation:
University of Texas at Dallas;
*
Murphy, Alexander R., University of Texas at Dallas, United States of America, [email protected]

Abstract

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During engineering design, different representations are used to convey information about a systems' components, functionality, spatial layout, and interdependencies. These varying representations may have an impact on the interpretation of a system and consequently the decision-making process. This paper presents a research study that tries to capture these different interpretations by investigating how designers divide a system into subsystem clusters. These subsystem clusters can be considered partitions of a set-in combinatorial mathematics. Given designers' subsystem clusters for three products across three representation modalities, three different analysis methods for finding the most likely partition from observed data are presented. Analysis shows that the Variation of Information analysis method gives the most coherent and consistent results for the search of a most likely cluster. In addition, differences in clustering behaviour are observed based on representation modality. These results show that the way an engineer or designer chooses to represent a system impacts how that system is interpreted, which has implications for the decision-making process during engineering design.

Keywords

Design theoryDesign cognitionDesign representationSystems thinkingHuman behaviour in design
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 3423 - 3432
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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