TITLE:
Enhancing Clothing Fit for Asian Women through Digital Transformation and Statistical Analysis
AUTHORS:
Saudia Haque Oishe, Zheng Liu
KEYWORDS:
Digital Pattern Creation, Statistical Analysis, Clothing Fit, Garment Customization, Apparel Industry Innovation
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.14 No.11,
November
5,
2024
ABSTRACT: This study focuses on designing a solution to the perennial issue of clothing fit in Fashion Industry using tools offered by digital technology and statistical analysis, in particular, the data gathered on Asian women (Bangladeshi and Chinese). The study reveals that managing information can significantly enhance the capability of the industry to cater to the needs of its consumers and increase diversity. It centers on the effectiveness of turning dressmaking patterns into digital ones, thus transecting from traditional cutting and stitching to remote techniques. This entails the requirement to have correct self-measures and probable errors, which can arise in the process. Thus, with the help of regression analysis, the study identifies, which measurements are incorrect and influence the fit of the clothes, and, therefore, digital pattern creation is more accurate. Altogether, it can be observed how digitalization and statistical methods are crucial to transforming the way clothes are created to approach an ideal standard of measurements that fulfill every customer’s needs to make operational and efficient the clothing sector.