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Enabling parametric design space exploration by non-designers

Authors :
Joaquim Jorge
José Pinto Duarte
Aaron D. Knochel
Eduardo Castro e Costa
Source :
Castro e Costa, E, Jorge, J, Knochel, A & Duarte, J P 2020, ' Enabling parametric design space exploration by non-designers ', Artificial Intelligence for Engineering Design, Analysis and Manufacturing, vol. 34, no. 2, pp. 160-175 . https://doi.org/10.1017/S0890060420000177
Publication Year :
2020
Publisher :
Cambridge University Press (CUP), 2020.

Abstract

In mass customization, software configurators enable novice end-users to design customized products and services according to their needs and preferences. However, traditional configurators hardly provide an engaging experience while avoiding the burden of choice. We propose a Design Participation Model to facilitate navigating the design space, based on two modules. Modeler enables designers to create customizable designs as parametric models, and Navigator subsequently permits novice end-users to explore these designs. While most parametric designs support direct manipulation of low-level features, we propose interpolation features to give customers more flexibility. In this paper, we focus on the implementation of such interpolation features into Navigator and its user interface. To assess our approach, we designed and performed user experiments to test and compare Modeler and Navigator, thus providing insights for further developments of our approach. Our results suggest that barycentric interpolation between qualitative parameters provides a more easily understandable interface that empowers novice customers to explore the design space expeditiously.

Details

ISSN :
14691760 and 08900604
Volume :
34
Database :
OpenAIRE
Journal :
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Accession number :
edsair.doi.dedup.....3e3b71345ebdaac9fd7d923764e81744
Full Text :
https://doi.org/10.1017/s0890060420000177