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The purpose of this paper is to analyze the stress‐relaxation behavior of different woven fabrics under constant torsional strain in a wrinkled state. For this purpose, a new method for determination of stress‐relaxation behavior of the fabric was used while keeping the torsional strain constant.

In this study, the behavior of stress relaxation of fabric is examined with modification of wrinkle force tester sophisticated electro‐mechanical method and fabricating a device which uses a computer and micro controller, with constant torsional strain by a rotational level of 9.1 turn/m in 280°, and in 300 s.

The results depict that stress‐relaxation percentage in fabric in weft alignment is more than warp alignment and the fabrics which tolerate more torsional force, possess less stress‐relaxation percentages. In this way, with increasing polyester percentage in fabric the scale of stress‐relaxation percentage decreases. Also, adoption of data derived from experiments with Maxwell model shows that the interlaced model is a suitable model for explaining the stress relaxation decline in fabric. Correlation coefficient of fabrics in weft alignment with Maxwell model is more than warp alignment.

This study has practical implications in the clothing as well as in technical textiles areas.

Knowing visco‐elastic properties is very important. However, there is no information available to study the stress relaxation of woven fabrics under the combined influences of compression and constant torsional strains.

This paper describes fabric inspection system aided by computer vision to detect and classify defects in circular knitted fabrics using different common texture-recognition methods, including co-occurrence matrices, the discrete Fourier transform, wavelets, Gabor, and clustering. The images of the fabrics were broadly classified into six classes: cracks, holes, vertical stripes, horizontal stripes, soil freckles, and defect-free. One hundred and twenty images (256 gray level and 100 dpi) containing 20 images of defect-free fabrics (rib 1x1) as well as 100 images corresponding to five different categories were used. In general, one-half of the images in each category were employed for training and the remaining images were used for testing.

The application of the clustering method applied in this work was found to be highly promising at identifying defects in knitted fabrics. With an overall success rate of 91.6%, the clustering method has a higher efficiency value than all of the other methods. In the case of the wavelet and Gabor methods, the results are acceptable. However, the overall success rates of the co-occurrence matrix and Fourier transform methods in recognizing defects in knitted fabrics are not acceptable.

The purpose of this paper is to evaluate some important parameters in plate buckling of fused interlining worsted fabric with different weight and laying‐up direction. The article compares the formability of fused fabric composite by two different methods (Lindberg's hypothesis and fabric assurance by simple testing method).

Plate buckling compression behavior of fused fabric composite is investigated using a special designed clamp according to Dahlberg's test method.

The result shows that fusible interlining lay‐up angle significantly influences on buckling parameters. It is indicated that the buckling behavior of fused fabric composite against lay‐up interlining direction is in accordance with interlining buckling behavior. The result of research suggests that the formability behavior of fused fabric composite with interlining lay‐up direction is predictable according to Lindberg's method.

Experimental design is limited at low speed. Further research works are needed to perform buckling behavior of fused fabric composites at higher speeds as well as under cyclic loading conditions.

Compression plate buckling behavior of fused interlining fabrics is predictable against interlining laying‐up direction. The result of this research could be used in the area of garment quality serviceability.

The purpose of this paper is to theoretically calculate and predict the needle penetration force (NPF) in woven denim fabrics with twill 3/1 weave pattern, based on the geometrical, physical, and mechanical properties of fabric and constituent weft and warp yarns.

In order to calculate the NPF by mathematical relations, the suggested model by Stylios and Xu (1995) is extended. While the needle penetrates into the fabric, the NPF is calculated on the basis of yarn tensile elongation, needle profile shape, and friction between needle and yarns. To accurately evaluate the developed model, nine different commercial denim fabric samples with various weft densities and linear density of weft yarns are produced, also five needles with different sizes are utilized. The NPF is measured in the successive cycle loading conditions similar to sewing machine process by using a designed and constructed instrument, which mounted on the Instron tensile tester.

Comparing the predicted and experimental values indicated that the accuracy of model to predict the NPF is partly acceptable (R2=0.734). To improve the developed model, in addition to the forces which applied on needle due to yarn elongation, the other forces such as friction between weft and warp yarns, and yarn resistance to bending in the near of the sewing needle, which resist against needle penetration, can be considered.

The fabrics with twill weave pattern have a complicated structure than plain pattern, therefore, in this paper the NPF of denim fabrics with twill 3/1 weave pattern were theoretically calculated based on yarn elongation. The spacing between centers of yarns in these fabrics is obtained by deriving a new formula. The NPF is measured on the Instron tensile tester to simulate sewing process.

This paper aims to predict the needle penetration force (NPF) in denim fabrics using the artificial neural network (ANN) and multiple linear regression (MLR) models based on the effects of various sewing parameters.

In order to design the ANN and MLR models, four parameters including fabric weight, number of fabric layers, weave pattern, and sewing needle size are taken into account as the input parameters and NPF as the output parameter. According to these parameters, 140 samples of data were resulted. Each sample was tested five times. From these 140 data (input-output data pairs), 112 were used for training the ANN and MLR models and 28 samples were used to test the performance of ANN and MLR. Also, the NPF was measured on the Instron tensile tester to simulate sewing process.

The results indicated that the NPF in denim fabrics can be well predicted in terms of sewing parameters by using ANN and MLR models, in which the ANN model exhibits greater performance than MLR (RANN=0.989> RMLR=0.901).

The NPF measurement method is limited at low speed.

Using the ANN model for forecasting NPF in denim fabrics can help the garment manufactures to produce high-quality denim products and improve the sewing process through reducing seam damage. The NPF could be also measured in the cycle loading conditions similar to sewing machine process by using a special designed tools mounted on the Instron tensile tester.

The purpose of this paper is to describe a unique approach to investigate the wrinkle force of textile structures in a cylindrical model.

In this research, an apparatus was designed and constructed in order to investigate the torsional and wrinkle behavior of textile structures in a cylindrical model under a different rotational level using data acquisition and micro‐controller systems.

In the light of research results, the fiber and fabric type, fabric physical and mechanical properties and imposed rotational level significantly contributed to wrinkle characteristics of worsted fabrics. It was noticed that with increase of rotational level, the wrinkle force, and energy increased along weft and warp directions. Wrinkle characteristics along warp direction exhibited greater values than in weft direction.

The study is aimed at determining wrinkle behavior of worsted fabrics under the combined influences of compression and torsional strains.

To investigate the relation of in‐plane fabric tensile properties with woven fabrics bagging behavior, a new test method was developed and a real time data acquisition and strain gauge technique were used. The bagging procedure was carried out while the woven fabric tensile deformations along warp and weft directions were measured. The fabric bagging behavior was characterized by bagging resistance, bagging fatigue, residual bagging height and residual bagging hysteresis. The experimental results show that the bagging load, work, hysteresis, residual hysteresis and fatigue are highly linearly correlated with corresponding parameters in warp and weft directions. An empirical relationship obtained between residual bagging height and bagging fatigue and resistance (R²=0.83) suggests that the proposed new test method is able to evaluate bagging behavior of fabrics.

The purpose of this paper is to theoretically compute and predict the needle penetration force (NPF) in woven denim fabrics with twill 3/1 weave pattern on the basis of geometrical, physical, and mechanical properties of yarns and fabric, and characteristics of sewing needle.

To predict the NPF by mathematical relations, the proposed models by Stylios and Xu (1995) and Lomov (1998) are extended for a twill woven structure. The NPF is calculated based on resistance forces due to yarn tensile elongation, yarn resistance to bending in the near of the sewing needle while the needle penetrates into the fabric, friction between weft and warp yarns, needle profile shape, and friction between sewing needle and yarns. In order to evaluate the obtained results, nine different denim fabric samples are produced, and five sewing needles with different sizes are used. The NPF is measured on the Instron tensile tester to simulate sewing process.

The results show that there is a good relationship between the predicted and experimental values of the NPF (R2=0.831, MSE=0.079, and MAPE=9.51 percent). Moreover, it is found that the performance of developed model to predict the NPF for needle sizes of 80, 90, 100, and 110 (Nm) is better than that of needle size of 120 (Nm). Generally, the developed theoretical model can predict the NPF in fabrics with twill 3/1 weave pattern.

The fabrics with twill weave pattern have a complicated structure than plain pattern. So, in this research work, the NPF of denim fabric with twill 3/1 weave pattern was theoretically predicted on the basis of yarn elongation, changing of yarn bent shape in the near of the sewing needle, and friction between warp and weft yarns. The NPF was measured in the successive cycle loading conditions similar to sewing machine process by using a designed and constructed instrument, which is mounted on the Instron tensile tester.

The purpose of this paper is to facilitate the production of cotton spandex woven fabric with some user-friendly properties like wearer comfort, super stretch and elasticity. The findings could contribute to ease spandex production and to optimize its property of elasticity. Stretch or a super stretch property is generally desirable, as it can increase the comfort level of those who wear it. In this experiment, the difficulties which were identified while manufacturing cotton spandex woven fabric resolved after identification.

In this experiment, three types of cotton spandex woven fabrics, with different composition and constructions, were used to find out their elastic properties. Temperature ranging from 160°C to 200°C with the machine speed of 20 to 26 MPM (meter per minute) was applied with an adjusted industrial setting with the facilities of a stenter machine to optimize the properties of cotton spandex woven fabric.

The findings establish that the temperature treatment closely compacted the elastic portions with cotton fibers, giving stability to the spandex yarn, which as a result, influenced cotton spandex woven fabric’s elastic properties, namely, stretch, growth and recovery. The consequences of temperature on cotton spandex yarns were assessed using a microscope, and the results were subsequently analyzed.

Because of the poor facilities in testing laboratory, only few tests with microscopic evaluation were conducted to assess the elastic performances of cotton spandex woven fabric.

It is a practice-based research, and the findings could be beneficial to personnel in the textile industry, who are responsible for the manufacturing of cotton spandex woven fabric.

This research could enhance the wearer’s satisfaction, with some comfort elastic properties, which can have a positive influence over spandex clothing industries.

This research establishes that heat setting had a progressive influence on the production of cotton spandex woven fabric and for the optimization of its elastic performances. This research opens a possible way for scholars to further study in this field.

The purpose of this paper is to predict the bagging recovery velocity of bagged denim fabric samples. Hence, the authors attempt to carry out a model highlighting and explaining the impact of some considered frictional parameters such as yarn-to-yarn friction expressed as weft yarn rigidity parameter and metal-to-fabric friction expressed by mean frictional coefficient parameter.

The statistical analysis steps were implemented using experimental design type Taguchi and thanks to Minitab 14 software. The modeling methodology analyzed in this paper deals with the linear regression method application and analysis. The predictive power of the obtained model is evaluated by comparing the estimated recovery velocity (theoretical) with the actual values. These comparative values are measured after the bagging test and during the relaxation time of the denim fabric samples. The regression coefficient (R2) values as well as the statistical tests (p-values, analysis of variance results) were investigated, discussed and analyzed to improve the findings.

According to the statistical results given by Taguchi analysis findings, the regression model is very significant (p-regression=0.04 and R2=97 percent) which explains widely the possibility of bagging behavior prediction in the studied experimental field of interest. Indeed the variation (the increase or the decrease) of the frictional input parameters values caused, as a result, the variation of the whole appearance and the shape of the bagged zone expressed by the residual bagging height variations. In spite of their similar compositions and characteristics, the woven bagged fabrics presented differently behaviors in terms of the bagging recovery and kinetic velocity values. After relaxation times which are not the same and relative to different fabric samples, it may be concluded that bagging behavior remained function of the internal frictional stresses, especially yarn-to-yarn and metal-to-fabric ones.

This study is interesting for denim consumers and industrial applications during long and repetitive uses. The paper has practical implications in the clothing appearance and other textile industry, especially in the weaving process when friction forms (yarn-to-yarn, yarn-to-metal frictions) and stresses are drastic. In fact, in terms of the importance to the industrial producers of the materials it helps to provide a first step in an attempt for a better understanding of the stresses involved in bagging of woven fabrics in general and denim fabrics particularly due to important frictional input contributions. They provide the basis for the development of fabrics that can withstand bagging problems. This research may also put forward improved methods of measuring bagginess as function of frictional parameters in order to optimize (minimize) their effects on the bagging behaviors before and after repetitive uses. These experimental, statistical and theoretical findings may be used to predict bagginess of fabrics based on their properties and prevent industrial from the most significant and influential inputs which should be adjusted accurately. This work allows industrial, also, to make more attention, in case of a high-quality level to ensure, to optimize and review yarn behaviors used to produce fabrics against drastic solicitations and minimize frictions forms during experimental spinning and weaving processes.

Until now, there is no sufficient information to evaluate and predict the effect of the yarn-to-yarn friction as well as metal-to-yarn one on the residual bagging behavior. Besides, there is no work that deals with the kinetic recovery evolution as function of frictional inputs to explain accurately the bagging behavior evolution during relaxation time. Therefore, this present work is to investigate and model the residual bagging recovery velocity after bagging test as function of the frictional input parameters of both denim yarn and fabric samples (expressed by the friction caused due to contact from conformator to fabric).