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This study aimed to use a scanner as a low-cost method for measuring the opacity of textile fabric. Textile fabrics must have specific ranges of opacity according to their uses for shirting, curtaining, etc. In this way, opacity is an important property in the textile industry. Conventionally, textile opacity is estimated using a spectrophotometer, which is an expensive method.

In this study a scanner was used as a low-cost method for measuring the opacity of textile fabric. The opacity was estimated by using red, green and blue (RGB) parameters of images of fabric against white and black background.

The accuracy of opacity estimation was improved by converting RGB into several color spaces. The best opacity estimation was obtained by using the XYZ color space. In addition, using a regression method, the best estimation was obtained by using a fourth-order polynomial regression with the LSLM color space.

The opacity of fabric has been measured by spectrophotometer, but in this study, the opacity of fabric was measured by scanner as a low cost device and also with novel and simple method. This method achieved acceptable accuracy for opacity estimation. The obtained result is comparable with spectrophotometer results.

Uses a general large displacement beam theory to formulate a finite element‐based numerical method for simulating fabric drape, manipulation and contact. Presents numerical results corresponding to real fabric materials. Shows a broad class of fabric mechanics problems including how these effects can be solved.

The purpose of this study is to use liposome technology in the treatment of fabrics textiles because of its efficient energy saving, reducing time and temperature.

The newly prepared lecithin liposome was used to encapsulate dyes for the purpose of increasing dyeing affinity. Different ratios of commercially available lecithin liposomes (1%, 3%, 5% and 7%) were used simultaneously in the dyeing of cotton and wool fabrics. The treated fabrics (cotton and wool fabrics) were confirmed using different analytical procedures such as scanning electron microscope (SEM), Fourier-transition infrared spectroscopy, ultraviolet protection factor, colour strength (K|S) measurements and fastness measurements.

The results show that increasing liposome ratios in dyeing baths leads to increased dyeing affinity for cotton and wool fabrics compared with conventional dyeing without using liposomes. In addition to that, the colour strength values, infrared spectra, SEM and fastness properties of non-liposome-dyed fabrics and liposome-dyed fabrics were investigated.

The research paper provides broad spectrum of green encapsulation fabrics using liposome technology to perform the dye stability, dye strength and fastness.

The purpose of this research is to design 3D print and analyze mechanical as well as microstructural behavior of interlaced fibrous structures using Dremel 3D45 additive manufacturing (AM) machine.

A series of plain and twill weave fabrics are designed using computer-aided design software Solidworks and printed using fused deposition modeling machines to determine the best model that could be printable. The structures were designed in such a way that the fabricated yarns with pure (PLA) were not sticking to each other in the fabric structure. The specimens were printed in vertical orientation and then tensile and three-point bending (flexural) tests were conducted for twill weave fabrics.

The tests showed that the mechanical strength was higher in the warp direction than in the weft direction. This difference was because of printing of continuous filament-like yarns in the warp direction and staple-like yarns in the weft direction. This orthotropic property of the material was verified by analyzing its microscopic structures via optical microscope.

Future work should include improvement of the structure and exploration of different polymers and their composites to increase the tensile, bending and other strengths to make the 3D-printed structures more flexible and stronger. Future research should also focus on the large-scale manufacturing of 3D printed fabrics.

This paper supports work on wearable 3D-printed fabrics. The 3D-printed fabric will also contribute to new applications and products such as liquid filters.

The research done in this work is new and original. This paper contributes to new knowledge by providing a better understanding of polymers and their 3D printing capabilities to form a complex fabric structure.

Examines the fifthteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

The main objective of this study is to highlight the relationship between RGB values of digital camera as a device-dependent color space and a device-independent CIE color space. Calibration and testing databases are the colorimetric specifications of colored polyester fabrics. The colored fabrics were dyed with a variety of disperse dyestuffs. Camera characterization was done based on the polynomial regression technique. The methods adopted in the study were non-linear filtering applied to camera RGB values and a polynomial regression function directly applied to the CIELAB space.

The performances of the methods improved by increasing the number of terms in the polynomial. The estimation errors of the linear polynomial regression to CIEXYZ, the nonlinear polynomial regression to CIEXYZ, the linear polynomial regression to CIELAB, and the nonlinear polynomial regression to CIELAB were 3.29, 4.43, 3.05, and 3.04 DE*ab respectively. The generalization capability decreased by increasing the number of terms in the polynomial regression. The best generalization capability was obtained by the linear polynomial regression to CIELAB. The best result was obtained by non-linear filtering while the second-best result was obtained by the polynomial regression to the CIELAB values.

There has been much discussion in the literature about the relationship between fabric “handle” and objective instrumental measurements of fabric low stress mechanical and surface properties such as fabric tensile properties, shear, bending, lateral compression, surface friction and surface roughness. But fabric “handle” is not really an inherent fabric property, rather it is a description of one of the ways in which people generally make a subjective assessment of some of the quality attributes of apparel fabrics, designed for particular end‐use applications. In contrast, fabric drape is an inherent mechanical property of a fabric. Fabric drape is that unique property which quantifies the ability of a fabric to bend simultaneously in more than one plane. In order to exhibit the property of drape, fabrics must be able to bend and shear simultaneously, thus distinguishing textile materials from paper or thin polymer films. Develops a fundamental mechanical analysis of fabrics bending under their own weight. The equations governing the shape of an elastic fabric cantilever are solved numerically. Discusses the implications for experimental measurement of fabric bending length and fabric bending rigidity in terms of these numerical solutions with negligibly small errors. Graphically presents profiles of the draped fabric cantilever. Makes a comparison of the numerical solutions with the approximate formulae derived by F.T. Peirce.

The purpose of this publication is to describe the possibility of using a scanner for the evaluation of color variation or color difference of textile fabrics. Initially, the color specification of colored fabrics were measured by spectrophotometers and the actual color differences between colored fabrics were calculated by the δE*ab color difference formula. Then, a scanner was used to take images of the textile fabrics. The obtained images were filtered for noise removal. The RGB values of the obtained images were used for the evaluation of textile fabrics color variation. Several methods were used to evaluate color difference by a scanner. The best prediction was obtained by the neural networks methodwith 1.014 δE*ab. Using this method, the accuracy of prediction for training sets was better than that for the testing sets. The performance of each method depends on the color difference values. so that, for low and high color difference, the best prediction was obtained by neural network, and for median color difference, the best prediction was obtained by the multi linear regression method. The obtained results show that the color variation of textile fabrics can be estimated by using scanner RGB variation.

Presents a mathematical treatment of the large‐scale bending behaviour of multi‐ply yarn. Based on the assumptions that: each individual fibre in the yarn has the form of a doubly‐wound helix; each fibre is an inextensible slender rod; and interaction between fibres is ignored. The yarn‐bending rigidity is calculated as an average rigidity of an assembly of coaxial helices. There is good agreement between the predicted and measured values of yarn bending rigidity for a wool worsted knitting yarn. Also predicts the position, curvature and twist components as well as the strain energy of the deformed fibre.