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.
|Number of pages
|International Journal of Clothing Science and Technology
|Published - 15 Jul 2020
Bibliographical noteFunding Information:
This work was supported by the Ewha Womans University Research Grant of 2018 and by the Korea Textile Trade Association. We also appreciated the cooperation of CLO Virtual Fashion LLC.
© 2020, Emerald Publishing Limited.
- 3D virtualization
- Classification system
- Cluster analysis
- Mechanical properties