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Enabling parametric design space exploration by non-designers

Published online by Cambridge University Press:  16 April 2020

Eduardo Castro e Costa Open the ORCID record for Eduardo Castro e Costa [Opens in a new window] ,
Joaquim Jorge ,
Aaron D. Knochel  and
José Pinto Duarte Open the ORCID record for José Pinto Duarte [Opens in a new window]
Eduardo Castro e Costa*
Affiliation:
Stuckeman School of Architecture and Landscape Architecture, The Pennsylvania State University, University Park, State College, PA, USA
Joaquim Jorge
Affiliation:
Department of Computer Science, University of Lisbon, Lisbon, Portugal
Aaron D. Knochel
Affiliation:
School of Visual Arts, The Pennsylvania State University, University Park, State College, PA, USA
José Pinto Duarte
Affiliation:
Stuckeman School of Architecture and Landscape Architecture, The Pennsylvania State University, University Park, State College, PA, USA
*
Author for correspondence: Eduardo Castro e Costa, E-mail: erc15@psu.edu
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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.

Keywords

Barycentric interpolationdesign space explorationmass customizationparametric modelinguser testing
Type
Research Article
Information
AI EDAM , Volume 34 , Special Issue 2: Thematic Collection: Design Cognition and Computing , May 2020 , pp. 160 - 175
Copyright
Copyright © Cambridge University Press 2020

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