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Title
An Improved Explicit Reference Modeling Methodology for Parametric Design
Author
Aranburu, Aritz
Justel Lozano, Daniel cc
Author (from another institution)
Camba, Jorge D.
Contero, Manuel
Publication Date
2023
Research Group
Centro de Innovación en Diseño
Other institutions
Purdue University
Universitat Politècnica de València (UPV)
Version
Postprint
Document type
Journal ArticleJournal Article
Language
English
Rights
© 2023 Elsevier
Access
Open access
Embargo end date
2025-08-31
URI
https://hdl.handle.net/20.500.11984/6118
Publisher’s version
https://doi.org/10.1016/j.cad.2023.103541
Published at
Computer Aided Design  Vol. 161. N. art. 103541
Publisher
Elsevier
Keywords
CAD reusability
Parametric modeling methodologies
Design intent
CAD quality
Abstract
The use of formal methodologies for parametric modeling has been shown to significantly improve the robustness and reusability of feature-based CAD models, particularly in response to changes, which h ... [+]
The use of formal methodologies for parametric modeling has been shown to significantly improve the robustness and reusability of feature-based CAD models, particularly in response to changes, which has implications in the entire product development process. One of these methodologies, explicit reference modeling, has been proven particularly effective in design scenarios involving complex geometry. However, certain design situations may lead to different interpretations of the methodology and the possibility of drastically different modeling alternatives at certain points in the process, some of which can become inefficient and hinder reusability. In this paper, we analyze the explicit reference modeling methodology through the lens of CAD quality and identify the key aspects that may lead to underperformance. We propose a new improved version of the methodology that maximizes model robustness and flexibility, while reducing regeneration time and intrinsic variability. Five modeling aspects are considered: the internal structure of functional geometries, subtractions, combination operations, replication features, and localized modifications. We validate our proposal through an empirical study in which 96 modeling paths for a parametric model were analyzed. [-]
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