SplineLearner: Generative learning system of design constraints for models represented using B-spline surfaces

A. Alper Tasmektepligil*, Erkan Gunpinar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Product design involves a computer-aided design (CAD) model with its design (dimensional) parameters. A generative design (GD) system can then be utilized to generate new designs by modifying these parameters. There is a need for a GD system to determine the visual validity of a design that is obtained after parametric modification. In this context, this paper introduces an approach to learn visual (i.e., design) constraints of a CAD model (represented using B-spline surfaces) by means of user feedbacks. A deformation technique (utilizing modification and limit curves) for B-spline surfaces is first introduced, which involves a few design (deformation) parameters. Via a generative learning process, the proposed system, SplineLearner, generates random designs, which are shown to user(s) for visual validity classifications. In a machine learning step, a mathematical model is computed that can perform prediction for a design to be valid or not. The mathematical model is also integrated into SplineLearner (after some user interactions) to prevent imbalances between the numbers of valid and invalid designs. As a proof of concept, B-spline surface models of a car body parts (hood, roof, side and trunk) are utilized, and two user studies are conducted to demonstrate the efficacy of the proposed method.

Original languageEnglish
Article number101478
JournalAdvanced Engineering Informatics
Volume51
DOIs
Publication statusPublished - Jan 2022

Bibliographical note

Publisher Copyright:
© 2021

Funding

The authors would like to thank Charlie C. L. Wang for his valuable discussions on learning design constraints via machine learning and The Scientific and Technological Research Council of Turkey for supporting this research (Project Number: 315M077 ).

FundersFunder number
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu315M077

    Keywords

    • B-spline surface
    • Computer-aided design
    • Constraint-based modeling
    • Design constraints
    • Generative design
    • Machine learning

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