This paper demonstrates the feasibility of objective measures to predict subjective feeling of fabrics and importance of surface-fiber profile on perceived touch of worsted fabrics. Objectively measured surface-fiber profile and geometrical roughness of fabrics were incorporated to predict perceived softness and warmth of touch of the fabrics. To quantify surface-fiber profile, we invented a measurement and analysis technique for surface fibers using image analysis system and fiber aggregate length (lA) was determined. Geometrical roughness (SMD) was obtained by calculating mean deviation of fabric thickness. A subjective evaluation was performed by 20 participants using nine-point semantic differential scale with a reference fabric. Discriminant models were developed using 21 fabrics to predict perceived softness and warmth of touch based on the objective measures of surface characteristics and verified using different set of 10 fabrics. The results showed that inclusion of surface-fiber profile enhanced the prediction models and the final hit ratios of the discriminate models were 75% and 80% for the perceived softness and warmth of touch, respectively. Relevance to industry This study shows that subjective perceptions of fabric softness and warmth of touch could be predicted using objective measures of geometrical surface roughness and quantified surface-fiber profile of worsted fabrics. The results and the methodology from this paper can be utilized to the product planning and finishing process in the textile industry.
All Science Journal Classification (ASJC) codes
- Human Factors and Ergonomics
- Public Health, Environmental and Occupational Health