Year: 2025
Type: article
Abstract: This study explores the simulation design of garment fabric texture to enhance wearing comfort within the framework of Industry 4.0. As personalized fashion becomes increasingly viable through digitalization and intelligent manufacturing, optimising fabric texture for comfort is crucial. The study adopts a comprehensive approach, integrating orthogonal design experiments, subjective wear trials, and objective measurements using thermal imaging, microclimate sensors, and pressure mapping. The research develops a predictive model for wearing comfort based on heat and moisture regulation, contact sensation, and pressure distribution. The findings highlight the significant influence of fabric material and gram weight interactions on overall comfort. These insights contribute to the advancement of smart textile design, enabling the production of garments that better meet human ergonomic and thermal needs and fostering innovation in fashion technology within the Industry 4.0 paradigm.
DOI: 10.4018/irmj.375009
Author: Jingjing Wang
Institution: Zhengzhou Technology and Business University
Language: English
Subfield: Polymers and Plastics
Field: Materials Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4410023676