Analysis and tensile-tear properties of abraded denim fabrics depending on pattern relations using statistical and artificial neural network models

The aim of this study is to develop new pattern denim fabrics and characterize the mechanical properties of these fabrics after abrasion load. Furthermore, tensile and tear strengths of these fabrics have been analysed by using the Artificial Neural Network (ANN) and statistical model. All denim fabrics were first abraded and subsequently tensile and tearing tests were applied to the abraided fabrics seperately. Actual data generated from the tests were analyzed by ANN and regression model. The regression model has shown that tensile strength properties of the abraded large structural pattern denim fabrics are generally low compared to that of the small structural pattern and traditional denim fabrics. On the other hand, when the abrasion cycles are increased tensile properties of all denim fabrics are generally decreased. Tearing strength of weft and warp in the abraded large structural pattern denim fabrics are between small structural pattern and traditional denim fabric. On the other hand, when the abrasion cycles are increased tearing strength properties in the weft and warp for all denim fabrics are generally decreased. The results from ANN and regression models were also compared with the measured values. It is concluded that almost all values from ANN are accurately predicted compared with those of the regression model. Therefore, we suggest that both methods can be used in this study as viable and reliable tools.     

Assessment of color strength and color difference values of polyester fabrics containing continuous weft yarns after abrasion

This paper assesses the color difference and color strength values (K/S) obtained for eight disperse-dyed polyester fabric samples with different fabric construction parameters (weft yarn type, weft yarn count, weft density and fabric weave) after four sets of abrasion cycles. Warp yarn type and count, warp density, and warp yarn twist are the same for all fabrics. Fabric samples are dyed in a commercial red disperse dye (C.I. Disperse Red 74:1) and four different abrasion cycles (2500, 5000, 7500, 10000) are used. TheK/S values of the abraided fabrics and color difference values between the control fabric (dyed but not abraided) and abraded fabrics are calculated. The main differences in theK/S and color difference values are observed between 0–2500 abrasion cycles. The high tenacity of the polyester fibers and continuous polyester yarns causes some fuzz but no pilling formation on the fabric surface that lead to increasedK/S values and color differences. Fiber dullness, yarn thickness, yarn density and fabric weave are concluded to have different effects on the appearance after abrasion.     

Evaluation of the structural properties of plain fabrics woven from various fibers using Peirce’s model

Peirce’s fabric model has been widely used to predict the structural behavior of various plain woven fabrics. The structure of plain woven fabric can be defined in terms of the warp yarn number, weft yarn number, warp fabric density, weft fabric density, warp crimp, and weft crimp. The warp and weft yarn diameters are calculated from the warp and weft yarn numbers, and the effective coefficient of the yarn diameter is defined by using this model. We have investigated structural properties, such as the effective coefficient of the yarn diameter, yarn crimp, and fabric thickness for two different fabrics in which the constituent yarns are assumed to be either incompressible or compressible. This model is also applied to various plain fabrics woven from cotton, rayon, wool, linen, nylon, acetate, polyester, and silk yarns.     

Classification of yarn interlacement pattern in fabrics using least square support vector machines

The purpose of this paper is to suggest an effective and reliable tool that can read through fabric images in the quest of deciphering yarn interlacement patterns by means of Least-Square Support Vector Machines (LS-SVM). A LS-SVM based binary pattern recognition system is formulated for identifying two modes of yarn interlacements viz., warp over weft or warp under weft and accuracy of the classifier was assessed by k-fold cross validation techniques. A comparative study establishes that LS-SVM shows better result than the standard SVM while classifying yarn interlacement patterns in fabrics. The proposed method has the potential to classify yarn interlacement patterns with possibility of extending it to designdecoding of diverse fabrics.     

Analysis and tensile characterization of air-entangled textured polyester woven fabrics depending on interlacement and yarn sets

The aim of this study was to understand the failure mechanism of two dimensional dry fabric structure considering yarn sets and interlacements. For this purpose, data generated on air-entangled textured polyester woven fabric under the simple tensile load and analyzed by developed regression model. The regression model showed that warp and weft directional tensile strengths of satin fabric were higher than those of plain and rib fabrics in unravel sample. This might be related to the number of interlacements of the fabrics. There was not a considerable difference between warp directional tensile strength of ravel and unravel satin fabrics, whereas weft directional tensile strength of ravel satin fabric decreased rapidly with respect to its unravel form. The satin fabric showed the highest warp directional tensile strength among the others. The lowest weft directional tensile strength was received from ribs fabric. In semi-ravel sample, all fabrics showed low warp and weft directional tensile strength values except in plain fabric. Warp directional tensile elongation of plain fabric was the highest in unravel sample. Satin fabric showed the highest warp directional tensile elongation in the ravel sample. Warp directional tensile elongations of all the fabrics in the semi-ravel sample became low. Weft directional tensile elongation of satin fabric was the highest in unravel sample. In addition, satin and plain fabrics showed the highest weft directional tensile elongations in the ravel sample. Weft directional tensile elongations of all the fabrics in the semi-ravel sample became low except in ribs fabric.     

Effect of weaving process on tensile characterization of single and multiple ends of air-entangled textured polyester yarns

The tensile properties of air-entangled textured polyester single and multiple yarn ends before and after weaving were analyzed. The effects of weaving process considering fabric unit cell interlacement and number of yarn ends were evaluated by regression model. For this purpose, plain, ribs and satin woven fabrics were produced. The yarns were raveled from fabrics, and the tensile tests were applied to these yarns. The developed regression model showed that the number of interlacement and crimp ratio on the warp and weft yarns influence their tensile strength. Tensile strength of raveled yarns decreased compared to that of the bobbin yarn due to the effect of weaving process. This property degradation on the ravel yarns considered process degradation. Generally, when the number of warp and weft yarn ends increases, the warp and weft yarn tensile strengths for each fabric type decrease, whereas the warp and weft yarn tensile elongations slightly increase. The results from regression model were compared with the measured values. This study confirmed that the method in the study can be a viable and reliable tool. The research finding could be useful those who work on preform fabrication.     

New insight into compressive shrinkage finishing in a garment company: The effects on physical,mechanical and colorimetric properties of cotton woven fabrics

Compressive shrinkage or compressive shrinkage finishing is one of the most important finishing procedures in the textile industry to improve the dimensional stability of cotton fabrics. Study of the physical and mechanical properties of compressive shrinkage finished fabrics could be useful for optimizing the treatment conditions. This research was carried out in a production line of a recognized garment company on cotton woven fabrics with two different woven patterns (twill and plain). The samples were first dyed with reactive and sulfur dyes in a jigger dyeing machine and finished with a silicone softener. The dried fabrics were then processed in a compressive shrinkage machine. Several physical and mechanical properties of the samples were evaluated including area shrinkage, crimp percentage, thickness, abrasion resistance, drapeability, mechanical and colorimetric properties. The results showed that the thickness of all treated samples increased due to compressive shrinkage. The fabrics were analyzed with a Martindale Abrasion Tester to determine the abrasion resistance. Interestingly, we noted an increase in the abrasion resistance. After the compressive shrinkage process, the strength of the plain woven fabrics decreased in the warp direction, but increased for twill woven cotton fabrics. On the contrary, the strength of all samples increased in the weft direction. Colorimetric evaluation of the samples showed that the effect of compressive shrinkage on the color of all samples was negligible.     

Reflectance prediction of colored polyester fabrics by a novel formula

This paper focuses on the reflectance prediction of colored (unicolored) fabrics considering relationship between fractional reflectance values and cover factors of fabrics woven from polyester yarns. A novel equation for the calculation of relation between fractional reflectance and cover factor was proposed and usage of the equation was assessed by reflectance measurements. 48 dyed polyester fabrics having different constructional parameters were used and fabrics differed from each other by their cover factors. Warp yarn type and count, warp density and warp yarn twist were the same but weft yarn count, weft yarn fiber count and weft density were different for the fabrics in experimental sub-groups. The reflectance measurements were conducted on the dyed fabric samples as well as on the individual yarn systems (warp and weft) of the same fabrics. The proposed equation was tested according to different fabric constructional parameters and reasonable results with the experimental data were obtained. The possibilities of general use of derived mathematical relations between theoretical and measured reflectance values were researched. The relation obtained was used to explain the effects of different constructional parameters on reflectance behavior of fabric surfaces.     

The effect of fabric balance and fabric cover on surface roughness of polyester fabrics

The effects of fabric balance and fabric cover on surface roughness values of textured polyester woven fabrics with different constructional parameters were investigated. The warp yarn properties (type, count and warp density) were kept constant while the effect of variation in weft yarn density and weave pattern were studied. Measurements were conducted on pre-treated white fabric samples and the results assessed in relation to their constructional properties. A general overview of the results showed that surface roughness values of polyester fabrics affected by fabric balance and fabric cover and the effects were related to fabric thickness, yarn densities, yarn crimp, positioning of yarns in fabric structure. A change in weave pattern from sateen to plain increased the fabric balance and fabric cover, but decreased the surface roughness. Similarly, an increase in weft density increased the fabric balance and fabric cover, but decreased surface roughness. In order to produce fabrics with smooth surface properties yarn density should be increased, yarn float lengths decreased, cover of fabrics increased and fabric balance improved.     

Assessing the relationship among fabric constructional parameters, fractional reflectances and cover factors of polyester fabrics by experimental and mathematical methods

This paper focuses on the assessment of the relation among constructional properties, fractional reflectances and cover factors of fabrics woven from polyester yarns. A novel equation for the calculation of the relation between fractional reflectance and fabric cover factor was proposed and the usage of the equation was assessed by reflectance measurements. 48 polyester fabrics having different constructional parameters were used and the fabrics differed from each other by their cover factors. The warp yarn type and count, warp density and warp yarn twist were the same but weft yarn count, weft yarn fiber count and weft density were different for the fabrics in the experimental sub-groups. The reflectance measurements were conducted on the pretreated but undyed fabric samples as well as on the individual yarn systems of the same fabrics. Fabrics with the same cover factors exhibited different fractional reflectances. Reflectances were found to be dependent on the cover factor as well as on yarn fiber fineness, yarn count, yarn density and fabric weave. The changes in crimp of the yarns according to different construction parameters also governed the changes in fractional reflectances of fabric surfaces. The proposed equation was tested according to different fabric construction parameters and it was concluded that fiber fineness and weave pattern were among the most important parameters which govern the total light reflectances from the fabric surfaces, although they are not incorporated in the calculation of the fabric cover factors. The proposed equation was used to explain the effects of these components on the reflectance behavior of the fabric surfaces and on fabric cover.     

Mechanical characterization of flocked fabric for automobile seat cover

In this study, the tensile and tearing properties of substrate, substrate with adhesive and flocked fabric were studied with developed regression model which explains the relationships between fabric forms and tensile and tearing strength of the flocked fabrics. Warp and weft tensile strengths of wet flocked fabric are generally higher than the warp and weft tensile strengths of dry flocked fabric due to the high wet properties of cotton yarn. Weft tensile elongation of the flocked fabric is generally higher than warp tensile elongation due to the higher crimp ratio of the flocked fabric in the weft direction. Warp and weft tearing strengths of wet form substrate with adhesive and flocked fabric are higher than those of dry forms of substrate with adhesive and flocked fabric. One of the reasons could be the decrease of inter-yarn frictional forces due to the lubrication effect of the wet form of acrylic adhesive in substrate with adhesive fabric. Generally, tearing strength of flocked fabric is low compared with substrate. It was concluded that the regression model used in this study could be viable and reliable tools and flocked fabric could be considered as an alternative seat cover material to use in automotive industry.     

Effect of filament size on the water transport of weft and warp knitted fabrics

Warp and weft knitted fabrics comprising polyethylene terephthalate/Co-PET sea-island bicomponent fibers were fabricated in this study. The knitted fabrics were treated in alkali solution to develop knitted fabrics composed of nano-scale filaments. The structural change and water transport behavior of the alkali-treated knitted fabrics were then compared. Results revealed that the filament diameters decreased from 20 µm to 850 nm after alkali treatment. The porosities of warp and weft knitted fabrics decreased by 4.8 % and 10.1 %, respectively, whereas their area densities increased by 68.8 % and 67.2 %, respectively. The wicking height and wicking rate of both types of fabric composed of microfilaments increased with prolonged alkali-treatment time. However, the water absorption properties such as absorption capacity and absorption rate of the knitted fabrics composed of nano-scale filaments significantly increased because of their low porosity and high area density.     

The effect of weft density on the skewness of the twill weave woven fabric

This experimental study investigates the effect of weft density on the skewness of the twill weave woven fabrics. A total of 12 rolls of woven fabrics - 2/2, 3/3 and 4/4 - twill weave, with 20, 22, 24 and 26 weft densities were produced and their skewness due to relaxation was measured. The measured values show that as the weft density increases from 20 to 26, the skewness decreases from 2.4, 2.9, 3.6 to 1, 1.1 and 1.15 respectively. This decrease supports the idea that the increase in weft density drops the effect of the weave type on skewness. In fact, this experimental work reveals that increase in weft density lowers the free spaces between the floats, shortens the float length and raises the shearing rigidity of the fabric and as a result the ability of the warp floats’ in-plane lever to move and skew is lowered.     

Predicting tensile strength of yarns required for producing PET/Cotton blended woven fabrics of a pre-defined tensile strength

This study was aimed at developing statistical models for the prediction of tensile strength of warp and weft yarns required for attaining a pre-defined strength of PET/Cotton blended woven fabrics. The models were developed based on the empirical data obtained from carefully developed 234 fabric samples with different constructions using 15, 20, and 25 tex yarns in warp and weft directions. The prediction ability and accuracy of the developed models were assessed by correlation analyses of the predicted and actual warp and weft yarn strength values of another set of 36 fabric samples. The analyses showed a very strong ability and accuracy of the developed statistical prediction models.     

Effects of loom characteristics on the physical properties of PET fabrics for emotional clothing

The fabric defects complained by garment manufacturers are stop marks, streaky phenomena on the warp direction, thickness variation and color differences between edges on the right and left sides of the fabrics, which are partly due to the tension variation of warp and weft directions. It is well known that these defects are related to the difference of fabric mechanical property according to the loom characteristics and fabric position such as center and both edges parts of the fabric, which affect garment formability and wearing performance of garment. This research is focusing about which factor is dominant for the difference of fabric mechanical properties which affects garment formability and wearing performance between loom characteristic factor and fabric position factor such as center and both edges of the fabric, which is affected by warp and weft tensions. For this purpose, two kinds of looms were selected, and warp and weft tensions during weaving were measured and the mechanical properties of the fabrics woven by two kinds of looms such as tensile, bending, shear, compression and surface properties were also measured according to the positions such as center and both edge parts of the fabric. These fabric mechanical properties were examined with warp and weft tensions according to the looms and were also analyzed according to the positions of the fabric woven by two kinds of looms. The warp tension on the vicinity of center parts of the looms was much higher than those on the vicinity of both edges of looms. It revealed that the warp tension difference makes differences of fabric mechanical properties such as tensile, bending, shear and surface properties except compressional property. And the differences of these mechanical properties according to the fabric positions and looms seem to make homogeneity of the fabric hand and tailorability of garment deteriorating.     

Mechanical properties of worsted fabrics for emotional garment to the rapier loom characteristics

This study examined the mechanical properties of worsted fabrics woven using various rapier weaving looms. For this purpose, the warp and weft yarn tensions during weaving were measured on the three types of rapier looms, and the fabric mechanical property changes due to the warp and weft tension differences were measured and analyzed according to the fabric position and particular rapier loom using the KES-FB system. The warp tension variation along the loom width direction in P-GTX loom showed the lowest value compared to FAST and THEMA looms. The warp tensions on the central part of the three types of looms were much higher than those on the left and right sides of the looms. The extensibility and bending rigidity of the fabric woven by P-GTX rapier loom showed lower values than those of FAST and THEMA looms, which appears to have originated from the low warp and weft weaving tensions of P-GTX rapier loom. On the other hand, the compressional property and shear modulus showed compromised results due to lateral deformation by compression and constraint deformation of the warp and weft by shear. The friction coefficient of the fabric surface woven by FAST loom showed the lowest value due to the flatter surface by the high warp tension. The mechanical properties of the fabric loaded by a high warp tension on the central part of the loom were also affected by the high weft yarn crimp due to the wider spacing between warp yarns by the higher warp tension during weaving, which makes the surface of the central part of the fabric flatter and smoother than the edge part of the fabric.     

Enhanced visualization of simulated woven fabrics

The woven fabric graphics designed with available computer aided design (CAD) systems using different colored warp and weft yarns look quite different from the appearance of their actual fabrics. To enhance the visual effects of designed woven fabric graphics, this paper reports a modified CAD woven fabric system, which allows users to design a fabric using parameters including fabric weaves, yarn number, yarn material, fabric count, crimp shape of interwoven yarns, and illumination. This enhanced system can design both yarns and fabrics, and consider the transitional color effect around interweaving points of warp and weft yarns. Its simulation image quality of woven fabrics has been greatly improved, and several textile mills and universities are currently using this woven fabric design system.     

Mechanical properties of denim fabric reinforced poly(lactic acid)

Denim, a twilled cotton fabric, was used to enhance the mechanical and thermal properties of poly(lactic acid) (PLA). The denim fabric reinforced composites with different numbers of denim layers were fabricated by using a hand layup method. The impact, tensile, and dynamic mechanical properties of the composites were observed with increasing denim layers to examine the reinforcing effect of denim fabrics. Numerical analysis was carried out to model the elastic modulus of the composite by using a commercial software. Three-dimensional geometry of the denim fabric reinforced PLA composite was generated through a CAD program, and the elastic modulus was calculated by applying uniform deformation on one surface. The impact strength, tensile strength, and thermal properties of the composites were improved by piling denim fabrics. The denim fabric reinforced composites exhibited outstanding impact strength due to the retarded crack propagation as well as large energy dissipation. The 3 layer denim reinforced composite showed best results among all specimens, and its impact strength, tensile strength, and tensile modulus were measured to be 82 J/m, 75.76 MPa, and 4.65 GPa, respectively. The PLA/denim composites have good mechanical properties and can substitute traditional composites such as glass fiber or carbon fiber reinforced composites.     

Application of artificial neural network (ANN) for prediction of fabrics’ extensibility

In the field of clothing technology, prediction of the fabric properties is very important because the fabric is the basic element of every clothing item. Knowing the fabric properties it is possible to predict fabrics’ behaviour during process of clothing manufacturing (in phase of cutting, sewing and ironing) as well as clothing items’ behaviour during usage. According to the fabrics’ characteristics and model design it is possible to predict appearances of the clothing items and their draping which can be presented with many computer simulations. In this paper extensibility of the fabric which appears during a small forces loading on the fabrics are investigated. Loading of small forces on the fabric appears in each phases of clothing manufacturing processes and during usage of clothing items. Investigations are managed on 50 fabrics which are weaving in twill weave and 100 % wool. The basic characteristics of fabric (density of warp and weft, mass per unit area, thickness) are defined according appropriate standard methods and tensile properties in the warp and weft directions are measured using KES-FB1 measuring system. Using an artificial neural network (ANN) prediction of extensibility properties of the fabrics are done, results are compared with experimental values and deviations are determined. ANN is an adaptive system that changes its structure based on external or internal information that flows through the network during the learning phase. They can be used to model complex relationships between inputs and outputs or to find patterns in data. Based on the implemented investigations, minimal deviations between experimental and predicted values are obtained and can be concluded that ANN can be used for prediction of the fabrics properties.     

Using artificial neural network to predict colour properties of laser-treated 100% cotton fabric

In this paper, artificial neural network (ANN) model was used for predicting colour properties of 100 % cotton fabrics, including colour yield (in terms of K/S value) and CIE L, a, and b values, under the influence of laser engraving process with various combination of laser processing parameters. Variables examined in the ANN model included fibre composition, fabric density (warp and weft direction), mass of fabric, fabric thickness and linear density of yarn (warp and weft direction). The ANN model was compared with a linear regression model where the ANN model produced superior results in prediction of colour properties of laser engraved 100 % cotton fabrics. The relative importance of the examined factors influencing colour properties was also investigated. The analysis revealed that laser processing parameters played an important role in affecting the colour properties of the treated 100 % cotton fabrics.