This approach offers an alternative method for size selection, one that accounts for the inherent variability in body measurements, thus providing a more tailored and accurate fit for consumers. This study aims to establish a dataset of ease coefficients for torso pattern design across various fabric types and body shapes to ensure proper garment fit. Data were collected from 120 women aged 18–30 in Ho Chi Minh City. Using principal component analysis, K-means clustering, discriminant analysis, and ANOVA via SPSS, participants were classified into four distinct body shape groups. A basic dress pattern was developed based on the average measurements of each group and simulated on different woven fabrics to assess fit and make necessary adjustments. The correlation between body-specific and average-group patterns was analyzed, resulting in a table of ease coefficients for multiple fabric types. Fit evaluations were conducted through 3D simulation and wearer feedback. The study provides ease coefficient data for the bust, waist, and hip areas of Vietnamese women aged 18–30, offering a foundation for the design of dresses and blouses in the fashion industry.
Nguyen et al. (Mon,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: