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.     

Predicting bending rigidity of woven fabrics using artificial neural networks

This paper reports an investigation on the predictability of bending property of woven fabrics from their constructional parameters using artificial neural network (ANN) approach. Number of cotton grey fabrics made of plain and satin weave designs were desized, scoured, and relaxed. The fabrics were then conditioned and tested for bending properties. Thread density in fabric, yarn linear density, twist in yarn, and weave design were accounted as input parameters for the model whereas bending rigidity in warp and weft directions of fabric formed the outputs. Gradient descent with momentum and an adaptive learning rate back-propagation was employed as learning algorithm to train the network. A sensitivity analysis was carried out to study the robustness of the model.     

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.     

Empirical modelling of tensile strength of woven fabrics

Aesthetic properties of fabrics have been considered as the most important fabric attribute for years. However, recently there has been a paradigm shift in the domain of textile material applications and consequently more emphasis is now being given on the mechanical and functional properties of fabrics rather than its aesthetic appeal. Moreover, in certain woven fabrics used for technical applications, strength is a decisive quality parameter. In this work, tensile strength of plain woven fabrics has been predicted by using two empirical modelling methods namely artificial neural network (ANN) and linear regression. Warp yarn strength, warp yarn elongation, ends per inch (EPI), picks per inch (PPI) and weft count (Ne) were used as input parameters. Both the models were able to predict the fabric strength with reasonably good precision although ANN model demonstrated higher prediction accuracy and generalization ability than the regression model. The warp yarn strength and EPI were found to be the two most significant factors influencing fabric strength in warp direction.     

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.     

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.     

Comparison of bending properties Co-woven-knitted and Multi-layered biaxial Weft-knitted fabric reinforced composites

Co-woven-knitted (CWK) fabrics and multi-layered biaxial weft knitted (MBWK) fabrics were prepared using glass filaments as both the warp and weft yarns and high tenacity polyesters as the stitch yarns with the same stitch length. Then the polyethylene resin was injected into the fabrics by vacuum assisted resin transfer molding to produce composites. Specific bending stress-displacement curves in the course and wale directions of the CWK fabric reinforced composites and the MBWK fabric reinforced composites were analyzed and their bending properties were also compared. Results indicate that the initial segments of all the specific bending stress-displacement curves for the CWK and the MBWK fabric reinforced composites are linear; then the specific bending stresses decrease with the displacements in a wave-like manner until sample destruction. The CWK fabric reinforced composites show plastic failure in course and wale directions, while the MBWK fabric reinforced composites show first fragile failure then plastic failure in course direction and show plastic failure in wale direction. Bending properties in the course direction of the CWK and the MBWK fabric reinforced composites are different from those in their wale direction, respectively. The CWK fabric reinforced composites are of smaller anisotropy than the MBWK fabric reinforced composites. By designing the buckling and distribution of the warp and weft yarns, the axial properties difference can be shortened.     

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.     

Predicting the air permeability of polyester/cotton blended woven fabrics

The aim of this study was to model the air permeability of polyester cotton blended woven fabrics. Fabrics of varying construction parameters i.e. yarn linear densities and thread densities were selected and tested for air permeability, fabric areal density and fabric thickness. A total of 135 different fabric constructions were tested among which 117 were allocated for development of prediction model while the remaining were utilized for its validation. Four variables were selected as input parameters on basis of statistical analysis i.e. warp yarn linear density, weft yarn linear density, ends per 25 mm and picks per 25 mm. Response surface regression was applied on the collected data set in order to develop the prediction model of the selected variables. The model showed satisfactory predictability when applied on unseen data and yielded an absolute average error of 5.1 %. The developed model can be effectively used for prediction of air permeability of the woven fabrics.     

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.     

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.     

Colour fading effect of indigo-dyed cotton denim fabric by CO2 laser

In this study, denim fabric was treated with CO₂ laser under different combination of laser process parameters, i.e. resolution and pixel time, in different irradiation directions, i.e. warp and weft directions. Experimental results revealed that the laser power increased with increment of resolution and pixel time. The colour fading effect was increased with the increase of laser power but an optimum colour fading effect was achieved. Meanwhile, the colour levelness of the laser treated denim fabric was good according to quantitative measurement. However, it was noted that the direction of laser irradiation did not affect the colour fading effect and colour levelness.     

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.     

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.     

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.     

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.     

Artificial neural network approach for predicting colour properties of laser-treated denim fabrics

In this study, artificial neural network (ANN) and linear regression (LR) approaches are proposed for predicting colour properties of laser-treated denim fabrics. Denim fabrics were treated under different combinations of laser processing parameters, including pixel time (μs), resolution (dot per inch) and grayscale (lightness percentage) as inputs. Colour properties, including colour yield (K/S sum value), CIE L*, a* and b* values and yellowness index were predicted as outputs in these approaches. Later, the prediction performances of two approaches were compared and the statistical findings revealed that ANN approach was able to provide more accurate prediction than LR approach, especially for L value. Moreover, among the three input variables, grayscale (lightness percentage) was found to be the most important factor affecting colour properties of laser-treated denim fabrics.     

Flexural stiffness of core spun cotton/spandex weft knitted structures under relaxation and machine washing treatments

In this research work, behavior of flexural stiffness of core spun cotton spandex single jersey, 1x1 rib and interlock fabrics was studied under relaxation and machine washing treatments. Results are compared with similar fabrics made from 100 % cotton. Fabric weight density increased with the progression of treatments and it is proportionate to the fabric tightness factor (stitch length^?1). Even though both types of fabrics had same machine set stitch lengths, cotton/spandex fabrics have shown the higher fabric weight densities than that of 100 % cotton fabrics. Although 1x1 rib and single jersey fabrics knitted with the same machine set stitch lengths, rib fabrics have given higher fabric weight densities than single jersey fabrics. Among the three knitted structures, interlock fabrics with higher machine set stitch lengths gave the higher fabric weights. Fabric stiffness and flexural rigidity have given higher values under the progression of treatments and it was found that higher values of stiffness have given by cotton/spandex knitted fabrics compared to their cotton fabrics. Fabric stiffness and flexural rigidity in wale direction were higher than that in course direction, but it is only observed in single jersey fabrics. However, 1x1 rib and interlock fabrics have shown an opposite behavior. It was also observed a positive correlation between TF (i.e.: stitch length^?1) and bending length/flexural rigidity in both fabric types. Lower flexural rigidities reported with single jersey structures and highest values gave with interlock structures of cotton/spandex and cotton fabrics.     

Analysis and off-axis tensile characterization of air-entangled textured polyester woven fabrics depending on unit cell interlacing frequency

The aim of this study is to analyze and determine the off-axis tensile properties of air-entangled textured polyester fabrics based on unit cell interlacing frequency. For this purpose, continuous filament polyester air-entangled textured yarn was used to produce plain, ribs and satin woven fabrics. The fabrics were cut from the warp direction (0°) to weft direction (90°) at every 15° increment, and tensile tests were applied to those of the off-axis samples. The strength and elongation results were introduced to the statistical model developed, and regression analyses were carried out. Hence, the effects of off-axis loading and interlacement on the directional tensile properties of the fabric were investigated. The regression model showed that off-axis loading influences fabric tensile strength. On the other hand, interlacement frequency is the most important factor for fabric tensile elongation. The results from the regression model were compared with the measured values. This study confirmed that the method used in this study as can be a viable and reliable tool. Future research will concentrate on multiaxially directional fabric and the probability that it will result in homogeneous in-plane fabric properties.     

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.