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The microspinning technology has generally been used for cotton in the case of small scale spinning test methods (50 gram fibres). One type of silk fibre waste -pierced cocoonprepared previously as short silk fibre with cut length of 35 mm is blended with cotton fibre to obtain further data concerning two blending techniques in this microspinning, and to compare pure and blended yarns. The intimate (before carding and drawframe blending as well as the roll settings in the drawing system are being examined. The silk content was changed at 0/100, 25/75 and 50/50 ratio for a yarn count of 30 tex. The physical properties, the irregularity and the fibre arrangement as terms of the Index of Blending Irregularity and the Migration Indices of the blended yarns have been studied. In addition, the effects of the blending techniques as well as those of the silk content have been brought to the fore.

People involved in the cotton industry, from growers to spinners, have been concerned about the problem of stickiness encountered during cotton processing from fibres to yarn. Many methods have been successfully developed to identify and measure stickiness and also to reduce the effect of these contaminations. Yet due to the poor fundamental scientific knowledge regarding the mechanisms of sugar adhesion on fibres, the major part of these methods is empirically based. Today, gaining knowledge about stickiness seems impossible without the help of a fundamental study on the accurate composition of honeydew and on the mechanisms of honeydew adhesion. This paper introduces a new quantitative analysis method for honeydew adhesion behaviour measurement. Adhesion measurement has been carried out on both individual sugar and sugar mixture and it reveals a strong influence of moisture content on adhesion energy and a weak influence of the type of metallic surface on adhesion energy.

A lot of fibre and fabric structures or finishing parameters influence the functional properties of fabrics. In order to assess the thermal properties of conventional polyester and microfibre types of fabrics the plate/fabric/plate method for conductivity or cool/warm feeling was used. Fabrics made of microfibres show lower heat conductance and therefore higher thermal insulation properties. Microfibre fibres exhibit a warmer feeling than conventional polyester fabrics depending on pressure, which may be due to the difference in the fibre and fabric surface in contact with the human skin.

Focuses on Korean garment manufacturing and the feasibility and benefits of introducing an expert system. Reviews previous literature on knowledge‐based system and describes in detail the stages followed in developing, constructing, testing, evaluating, integrating, implementing and maintaining the expert system. Concludes that an expert system could be used to solve various garment manufacturing problems and would contribute to garment quality improvement through a standardized apparel production process.

Empire style fashion, Greek-Roman style robe with bare shoulder and chest and short sleeved with long gloves which created a slim silhouette, was worn even in winter season in Europe, where average temperature is 0-5°C. Most women suffered with catching cold and thousands caught flu and tuberculosis of the lungs, called muslin disease. The purpose of this paper is to find out clothing insulation of the robe by measuring the thermal resistance and to guess how cold they felt in this robe in winter time.

The authors performed the investigation on original robe shape with based on historical evidence and data, such as drawings, sketches, pattern books and sewing books, and reproduced a representative robe costume and tested its thermal insulation. The fabrics of robe were thin wool, silk and cotton following the literature evidence and preserved costume. Thermal insulation of the robes was measured using thermal manikin with the test method ISO 15831. The authors analyzed the thermal insulation of reconstructed robes with an inner cotton breech as for daily use and tested them wrapped with cashmere shawl on manikin shoulder as for severe cold weather.

The dress robes had the range of 0.61-0.67 clo regardless of the type of fabric materials, and 0.80-0.81 clo with the cashmere shawl. These values were not enough for women to keep body temperature or comfort in winter time.

This study combined fashion historic theory for costume reproduction with clothing science and technology for thermal insulation. Combination of costume history, construction technology and measurement engineering is the ingenious idea, and the combination of historical and scientific research evidences interdisciplinary originality.

The purpose of this paper is to elucidate the stress-strain relationships of single-jersey knitted fabrics from uniaxial tensile test followed by deformation behavior using finite element analysis. In order to elaborate the study, high, medium and low tightness knitted fabrics were selected and deformation of fabrics analyzed in course, wales and bias directions (0, 45 and 90 degrees).

This study focussed on uni-axial tensile test of produced test samples using Instron 6021 tester and a development of single-jersey knitted loop model using Auto Desk Inventor software (ADI). The knitted fabric material properties and knitted loop model was imported to ANSYS 12.0 software.

Due to structural changes the tightness and thickness of knitted fabric decreases with increase in loop length The tensile result shows maximum breaking strength at course direction (13.43 kg f/mm2 at 2.7 mm) and maximum extension at wales direction (165.77 kg f/mm2 at 3.3 mm). When the loop length increases, the elongation of fabrics increased and load carrying capacity of fabrics reduced. The Young's modulus, Poisson's ratio and shear modulus of fabrics reduced with increase in loop length. The deformation of fabrics increased with increase in loop length. The increase in loop length gives large amount of structural changes and it is due to slacking or jamming in loops and loosening in dimensions. When comparing the deformation results, the variation within the fabric is higher and structural damage little more when increasing the loop length of the fabric.

From ANOVA test, stress and strain distribution was statistically significant among course, wales and bias directions at 95 percent confidence level. The values got from Instron test indicates that testing direction can alter its deformation. In deformation analysis, comparing both experimental and prediction, high amount of structural changes observed in wales direction. The used tetrahedral elements can be used for contact analysis with high accuracy. For non-linear problems, consistent approach was proposed which makes the sense to compare with experimental methods. The proposed model will make possible developments and the preliminary validation tests shows good agreement with experimental data.

The purpose of this paper is to propose a theoretical model to predict the mechanical behaviour of needle punched heavy geotextiles in uniaxial tensile test.

The model was constructed using theory of layered composite materials and finite element method. The properties of a reference fabric were used as initial data in theoretical calculations and a commercially available finite element program was chosen to carry out stress analysis. A comparison is made between theoretical calculations and experimental data to evaluate the deformation mechanism of geotextile fabrics in uniaxial tensile test.

The results indicate that compatible data were predicted in terms of stress values and stress distribution of fabrics. The inconstant lateral contraction of nonwoven fabrics in tensile test is also successfully simulated by the model. However, in the case of elongations, the model could not predict the strains of heavy geotextiles accurately.

The study aims at predicting the mechanical behaviour of needle punched heavy geotextiles by using the structural and mechanical properties of a “reference fabric” instead of constituent fiber properties.

Currently, textile industrialists have to consider the sensory aspect in their design and manufacturing specifications. To describe the sensory quality of products, sensory evaluation does exist and is widely used in the food and cosmetics areas. These methodologies have been successfully transposed to tactile evaluation of textile fabrics for different textile materials: plain weave fabrics with different post‐treatments and non‐woven are used for medical gowns and drapes. In our study, we have asked our trained panel composed of nine assessors to score a list of already defined sensory attributes for different knitted fabrics made of silk/cotton blends. The spinning parameters which have been changed are the type of silk fibre (three types), blending techniques – intimate and draw frame blending – and the silk content. All these parameters can more or less influence the tactile perception of the final knitted fabric. In this paper, the results of our analysis are presented and discussed in order to answer questions such as: “Are these two fabrics different?”, “What kind of difference is there?” or “What are the sensory characteristics of these fabrics?”. The concrete steps of the evaluation will be presented and specifically the training and performance analysis of the panellists who were obliged to adapt their evaluation procedures to small knitted samples. The protocols used to carry out fabrics description and comparisons when all assessors cannot evaluate all the products under study will also be detailed.

This study aims to analyse cellulose fibres extracted from the pseudo-stems of Cymbopogon citratus and evaluate their properties in non-woven fabric production.

The water retting method was used for fibre extraction, and intrinsic fibre qualities were examined to assess their suitability for textile applications. A thermal bonding technique, using a hot press machine and polylactic acid powder as a binder, was applied for non-woven fabric development.

The retted fibres had an average length of 156 mm and a fineness value of 5.73 tex. The fibre’s tenacity and elongation values were 1.33 gf/denier and 12.78%, respectively. Fourier transform infrared analysis confirmed the presence of major cellulose components. The fibre’s crystallinity and friction coefficient were 50% and 0.3, respectively. C. citratus fibre exhibited hygroscopic characteristics with a moisture regain of 10.65%. Experimental non-woven fabrics (70% C. citratus fibre, 30% polylactic acid powder) demonstrated consistent weight and thickness, with variations in tensile strength. Moisture regain values for non-woven fabrics were approximately 7.6%.

The features of C. citratus fibre, obtained with the water retting process, exhibited suitability for textile applications. Three experimental non-woven fabrics comprising of C. citratus fibre and polylactic acid powder were produced with three different pressing temperatures. The tensile strength properties of these fabrics were influenced by pressing temperature.

The defect detection problem of color-patterned fabric is still a huge challenge due to the lack of manual defect labeling samples. Recently, many fabric defect detection algorithms based on feature engineering and deep learning have been proposed, but these methods have overdetection or miss-detection problems because they cannot adapt to the complex patterns of color-patterned fabrics. The purpose of this paper is to propose a defect detection framework based on unsupervised adversarial learning for image reconstruction to solve the above problems.

The proposed framework consists of three parts: a generator, a discriminator and an image postprocessing module. The generator is able to extract the features of the image and then reconstruct the image. The discriminator can supervise the generator to repair defects in the samples to improve the quality of image reconstruction. The multidifference image postprocessing module is used to obtain the final detection results of color-patterned fabric defects.

The proposed framework is compared with state-of-the-art methods on the public dataset YDFID-1(Yarn-Dyed Fabric Image Dataset-version1). The proposed framework is also validated on several classes in the MvTec AD dataset. The experimental results of various patterns/classes on YDFID-1 and MvTecAD demonstrate the effectiveness and superiority of this method in fabric defect detection.

It provides an automatic defect detection solution that is convenient for engineering applications for the inspection process of the color-patterned fabric manufacturing industry. A public dataset is provided for academia.