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Article
Publication date: 2 March 2020

Jimin Kim, Yun Jeong Kim, Myounghee Shim, Youngmin Jun and Changsang Yun

This study aims to create a classification system enabling users of 3D virtualization software to intuitively perceive the drapability of fabrics.

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Abstract

Purpose

This study aims to create a classification system enabling users of 3D virtualization software to intuitively perceive the drapability of fabrics.

Design/methodology/approach

1,001 fabrics were used, and thickness, bending property, and tensile strength were identified as main mechanical properties influencing drapability; they have been set as independent variables in the model established to predict drape coefficient.

Findings

A system to classify fabrics into eight groups by drapability was suggested by a cluster analysis, and a multinomial logistic regression analysis was used to set a model that allows users to predict which group a fabric belongs to from its mechanical properties.

Originality/value

This paper provided basic materials for the construction of a virtual clothing simulation system, which is believed to contribute to cost and time savings in decision-making by reducing the number of trials and errors required by the conventional approach.

Details

International Journal of Clothing Science and Technology, vol. 32 no. 4
Type: Research Article
ISSN: 0955-6222

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