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.     

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.     

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.     

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.     

Electromagnetic interference shielding effectiveness of SS/PET hybrid yarn incorporated woven fabrics

A detailed study of electromagnetic shielding effectiveness (EMSE) of woven fabrics made of polyester and stainless steel/polyester blended conductive yarn was presented in this research work. Fabrics with different structures were analyzed and their shielding behavior was reported under different frequencies. Shielding efficiency of fabric was analyzed by vector network analyzer in the frequency range of 300 kHz to 1.5 GHz using coaxial transmission line holder. The effects of different fabric parameters such as weft density, proportion of conductive weft yarn, proportion of stainless steel content, grid openness, weave pattern and number of fabric layers on EMSE of fabrics were studied. The EMSE of fabric was found to be increased with increase in proportion of conductive yarn in the weft way. With increase in overall stainless-steel content in the fabric, the EMSE of fabric was increased. As such weave is considered, it did not have significant effect on EMSE of fabrics. But fabric with lower openness and aperture ratio showed better conducting network, hence better shielding. With increase in number of layers of fabric and ply yarns, EMSE of fabric was increased.     

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.     

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.     

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.     

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.     

Simulation of the weave structural design of synthetic woven fabrics

This study surveys the basic procedure of data base system of the fabric structural design which can be linked with existing pattern design and garment design CAD systems. For this purpose, the theoretical and empirical equations related to the fabric structural design are analyzed and discussed with various fabric specimens. The fabric structural parameters such as weave density coefficient, cover factor and yarn density coefficient of various kinds of fabrics are calculated using the empirical equations. These calculated fabric structural parameters of many kinds of polyester and nylon fabrics are compared and discussed with weave pattern, and materials such as polyester and nylon. Furthermore the difference between fabric structural parameters calculated by empirical equations are analyzed with polyester and nylon fabrics as a basic study for data base system of the fabric structural design. Finally, the weave density coefficients of polyester and nylon fabrics were analysed and discussed with shrinkages of dyeing and finishing processes, and also surveyed according to the weaving company and weave structural parameters such as weave pattern and denier.     

Handle,fit and pressure comfort of silk/hybrid yarn woven stretch fabrics

Hybrid yarn was produced by twisting silk with nylon covered lycra yarn. Silk of 20 D in warp and hybrid yarn in weft was woven to develop lustrous woven stretch fabrics for sari blouse. Silk and hybrid yarn fabrics were produced in three different weaves namely plain, crepe and sateen. An in-depth study was carried out to understand the effect of weave on thermal comfort; low stress mechanical properties, total hand value and stretch properties. Nine blouses (3 samples× 3 figures) were constructed from three different woven stretch materials for fit assessment and objective pressure comfort test. The effect of fabric weave, low stress mechanical properties, total hand value and stretch properties on fit and pressure comfort of silk/hybrid yarn stretch fabrics were analyzed. Sateen weave silk/hybrid yarn stretch fabric shows higher total hand value, stretch properties and better thermal comfort properties. Sateen and crepe weave stretch fabrics provided good fit. Sateen weave fabric exerted lower clothing pressure value in the range of 3-12 mmHg at all body locations in standing position and in different postures.     

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.     

New production method for a plain weave figured fabric

A new production method for figured fabric has been developed. The figured fabric generated in this study is a plain weave piled fabric and it shows the same figure on both sides unlike those fabrics woven on dobby or jacquard looms. It is woven by a specialty yarn called the chenille yarn which is obtained by separating each warp of a base fabric woven in leno structure. The base fabric is woven by inserting different colored weft each time in a certain sequence arranged according to the target figure image. A CAD software and a computerized controller have been developed to control all the motions of a conventional rapier loom and to handle the numerous weft insertion schedule efficiently.     

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.     

Influence of the deformation mode on seam slippage in woven fabrics

In the present study the influence of the deformation mode, of the specimen elongation deformation, of the fabrics?? weave type, of fabrics?? direction and of the position of seam allowances in respect to the stitching line on the seam slippage in the raw plain, twill and combined-twill weave fabrics was investigated. Fabrics were woven with the warp yarn of 20×2 tex 70 % cotton and 30 % PES blended 2-ply spun yarn and the weft yarn of 18 tex 100 % PES folded multifilament yarn using jacquard weaving machine ??Lindaucer DORNER GmbH??. Seam slippage of the investigated woven fabrics was determined using the new simple and compact technical device suitable to test fabrics for seam slippage property within five different deformation modes: an uniaxial tension of seams with opened seam allowances on the surface of metal table; an uniaxial tension of seams with bent to one side allowances in respect to stitching line on the surface of the metal table; an unrestricted uniaxial tension of seams; a bagging of seams with bent to one side allowances in respect to the stitching line using the plastic hollow cylinder; a bagging of seams with opened seam allowances using the plastic hollow cylinder. The results of the research had proved that seam slippage of the investigated woven fabrics was dependent on the deformation mode, on the elongation of sewn specimens, on the location of allowances in respect to the stitching line, on the fabric weave type as well as on the woven fabric direction.     

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.     

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.     

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.