Consumers use their sense of touch instinctively to evaluate a garment's quality and faculty for specific use. The roughness of textiles is an important parameter for customers' choice of garments. This work focused on surface roughness of woven fabrics. A Textile Surface Tester (TST) was used in this study. For surface height variation (SHV) characterization, the standard roughness parameters described in the ISO 4287 was frequently used. During this analysis, we examined the effect of different parameters of manufacturing and finishing samples on the variation in surface roughness. It was found that the fabric type had an important effect on surface roughness as well as the weft count of woven samples, while chemicals treatments, as coating with different commercial products via ink-jet printing and drying processes, did not affect this parameter.
The present paper concerns the statistical analysis of the surface roughness evaluation of knitted fabrics by the Textile Surface Tester. The main objectives were, firstly, focused on investigating the effect of knitted fabrics structural factors and the test conditions on the surface absolute roughness, the total roughness and the standard deviation. Secondly, the relationship between sample characteristics (face, yarn count, loop length), the test conditions (the force and the slipping speed of the sensor feeler on the sample and signal sampling time), and the surface roughness parameters were analyzed and modeled through regression analysis. The combined effects of the input parameters and their two-way interactions on the test bench outputs were investigated using the analysis of variance (ANOVA). The percent contribution ratio was used to show the influence of inputs and their interactions on surface roughness parameters. The results show how much surface roughness is mainly influenced by the knits structural factors. Also, it is underlined that the applied force by the sensor feeler on the fabric has an important effect on outputs. Finally, the sensor slipping speed on the sample and the signal sampling time have no important effects on outputs. Models were developed using experimental results from a full factorial experimental design. The adjusted coefficients of determination R 2 adj were found to be greater than 80%.
A Textile Surface Tester was used in this study to measure the surface roughness of weft knitted fabric. The aim of this work is to examine the influence of fabric parameters and test conditions on the sample's surface roughness. In this investigation, tests were carried out on single jersey knitted fabric for outwear. The measurement was carried out via an inductive sensor for displacement which produces signal in relation to the sample relives. We applied decomposition via the Fourier and the wavelet transforms to extract useful data from the produced signals signal. The surface roughness parameters were calculated according to the standard ISO 4287 (1997). Implications of the results on the influence of the stitch length and the yarn count on surface roughness are discussed.
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