Development of chafe resistance apparel

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Authors

Hafsa Jamshaid¹ , Naseer Ahmad¹ , Uzair Hussain¹ , Awais Khan¹

Poster summary: Clothing comfort is the first and foremost property of the fabric considered by consumers, especially in apparel. As the under-wear fabrics come in direct contact with the skin so it demands better chafe resistance properties. Better comfort and frictional properties in the under-wear fabrics are one of important requirements. The objective of this study is to investigate the effect of the different blends (%) of cotton, Coolmax, and micro polyester fibers and two linear densities i.e., 24/1s and 30/1s (Ne/English count) on the friction and comfort properties of the knitted underwear. It is concluded that a combination of natural and synthetic fibers with finer linear density results in better-performing fabrics with regard to friction and moisture management. Sample containing 50% cotton and 50% micro-polyester with 30/1s yarn count was declared as the best samples based on the Grey Relational Analysis which is a multi-response optimization technique.

References

H. Jamshaid, N. Ahmad, A. Khan, and U. Hussain, “Multi-response Optimization by Using Taguchi Based Grey Relational Analysis to Develop Chafe Resistance Underwear,” Journal of Testing and Evaluation https://doi.org/10.1520/JTE20220257
R. Baby, K. Mathur, and E. DenHartog, "Skin-textiles friction: importance and prospects in skin comfort and in healthcare in prevention of skin injuries," The Journal of The Textile Institute, vol. 112, pp. 1514-1530, 2021/09/02 2021.
H.jamshaid , N.Ahmed U.Hussain and R.Mishra. "Parametric optimization of durable sheeting fabric using Taguchi Grey Relational Analysis" Journal of king saud univeristy-Science , Volume 34 .2022.
Bannu Ozgen and Sevda Altas. "Investigation of Thermal comfort , Moisture Management and Handle Properties of Knitted fabrics made of various fibers", Tekstil vs Konfeksiyon journal , volume 24(3) , 2014.

Additional information

Data availability statement: The datasets generated during and / or analyzed during the current study are available from the corresponding author on reasonable request.

Creative Commons license: Copyright © 2023 Jamshaid et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.