Filament Fineness Research Articles

Effects of sewing thread filament fineness on moisture management properties of seams

Effects of sewing thread filament fineness on moisture management properties of seams

A STUDY ON PERFORMANCE OF POLYPROPYLENE CARPETS PRODUCED WITH DIFFERENT FILAMENT FINENESS AND SLIP ADDITIVE RATIOS UNDER STATIC LOADING

Polypropylene, which is one of the most used polymers in machine carpet production as pile yarn, has some disadvantages need to be developed, such as lower resilience, flattening, matting etc. For this reason, there are so many studies in order to improve the inferior properties of polypropylene in carpet industry. In this study, eight carpet samples were produced by polypropylene BCF yarns with two filament fineness (3.7 and 9.5 dpf) and four ratios of slip additive (0 wt%, 0.5 wt%, 1 wt%, 2 wt%). In order to determine the effects of different filament fineness and additive percentage on thickness loss and resilience, carpet samples were exposed to short-term static loading test. According to the results, samples with 9.5 dpf filament fineness had lower thickness loss values compared to those of samples with 3.7 dpf filament fineness. Besides, the resilience behaviours of samples with 9.5 dpf filament fineness were also obtained to be better than samples with 3.7 dpf filament fineness. In consideration with slip additive percentages, although a trend was not observed between the increased additive ratio and mechanical responses of carpets, a difference was obtained between pure and 2 wt% additive blended samples. The blended samples with 2 wt% additive had shown lower thickness loss and higher resilience compared to neat samples.

Investigation of the effects of filament fineness and disc type on yarn physical and mechanical properties of DTY polyester yarns

Investigation of the effects of filament fineness and disc type on yarn physical and mechanical properties of DTY polyester yarns

Study on thermal comfort behaviour of seams made of micro-denier polyester sewing thread for high active sportswear

This work aims to investigate the thermal comfort behaviour of polyester seamed fabric regarding the change in sewing thread filaments fineness for two different seam classes: seam 514 and seam 607. Five seamed fabric samples were constructed with using micro-denier polyester filament of 16.66 tex made of five different filament numbers (38, 48, 108, 144 and 288). It was noticed that the seam thermal properties, air and water vapour permeability, and wicking can be improved if the seam is constructed with using the micro-denier polyester sewing thread. It was also found that the investigated properties increase with the increase in the sewing thread filament fineness on the seam line. The statistical results have also shown that the sewing thread filament fineness is significantly affecting thermal behaviour of the seamed fabric.

Effects of filament fineness and disc type of drawn textured polyester yarns on carpet resilience and appearance retention performance

The deformation on the carpet texture is generally caused by foot traffic, furniture loading and soiling. The resistance of the carpet to texture distortion depends on the pile yarn characteristic and morphology. In this study, the resilience and appearance retention of carpet samples produced with drawn textured polyester pile yarns which are widely used in the carpet industry, were investigated. In this context, 6 pile yarns were produced with 3 different filament finenesses (3.13, 2.08 and 1.56 dpf) and 2 different disc types (polyurethane and ceramic). The carpet specimens were applied to compression/recovery, dynamic loading, hexapod appearance retention and soiling tests. According to the results, the carpet sample with 2.08 dpf filament fineness and produced by polyurethane disc type showed less thickness loss and better compression recovery results. Hexapod test results showed that the carpet samples with the finest filament had the lowest appearance retention levels. For soiling performance, it was observed that carpet samples with coarser filaments had slightly less staining and disc type had a no significance effect.

Modeling the air permeability of pile loop knit fabrics using fuzzy logic and artificial neural network

Pile loop knit fabrics have attracted attention in biomedical applications particularly due to their unique porous three-dimensional structures. Since there is a close relationship between pore characteristics and air permeability of a textile structure, the control of air permeability property during production would improve production planning when designing new knitted fabrics. This study deals with the development of an Artificial Neural Network (ANN) model, and a Fuzzy Logic (FL) model for predicting the air permeability of pile loop knit fabrics. For this aim, pile loop knit structures with different areal densities were produced by using textured polyethylene terephthalate (PET) yarns from four different filament fineness. Multiple linear regression (MLR), FL, and ANN model analyses were done. The root mean square error of the MLR, FL, and ANN were found to be 14.934, 12.41, and 2.418, respectively. Thus, the ANN model provided superior performance over the MLR and FL model in predicting air permeability.

Influence of spacer filament fineness on indentation characterizations of warp-knitted spacer fabrics for mattresses

Mattress plays an important role in the quality of human sleep, warp-knitted spacer fabric (WKSF) is a rather important mattress material, this paper explored the indentation state of WKSFs of 20 mm thickness and 0.12, 0.15, 0.18, and 0.25 mm spacer filaments under the action of curved surface pressure by using spherical compression tests and finite element simulations, with the combination of three-dimensional and non-uniform pressure characteristics exerted on the mattress by the human body when lying down. Tests and simulations analysis would be shown in four aspects: firstly, when the spherical indenter acts on the WKSFs, the compressive stress, Indentation Force Deflection (IFD) and support factor (SF) of the WKSFs increase as the spacer filament fineness increases; secondly, the compression depth of WKSFs should be controlled within 40% when used as mattresses to obtain good compression comfort; thirdly, A warp-knitted spacer fabric with a 0.25 mm spacer filament fineness provides both comfort and pressure resistance and better meets the needs of most people for a spacer fabric for mattresses.

The effect of denier per filament (DPF) on low-stress mechanical and transmission behaviour of polyester filament fabrics

This study aims to explain the effects of denier per filament (DPF) on low-stress mechanical properties and the transmission behaviour of multifilament woven polyester fabrics. To observe the effect of filament fineness precisely, poly (ethylene terephthalate) filament yarn having a DPF 0.6, 0.7, 0.9. 1.0, 1.1, 1.4, 2.1 from the same batch of polymer are produced. The filament yarns are converted to the fabric with constant areal density. The low-stress mechanical properties of fabric samples are measured by using the Kawabata evaluation system (KES-FB). Air transmission and moisture vapour transmission behaviour are recorded by air permeability tester TEXTEST FX 3300 and moisture vapour permeability tester PERMETEST. The air permeability of fabric is positively correlated with DPF in fully drawn yarn (FDY) and draw textured yarn (DTY) forms. However, the air permeability is found significantly higher in DTY yarn than FDY having the same DPF.

Micro-polyester filament yarns and their fabric moisture transport characteristics for sportswear

S.M. Udaya Krithika, C. Prakash Department of Fashion Technology, Sona College of Technology, Salem/India M.B. Sampath Department of Textile Technology, K.S. Rangasamy College of Technology, Namakkal/India M. Senthilkumar Department of Textile Technology, PSG Polytechnic College, Coimbatore/India In this present study, the effect of filament fineness on yarn wicking and the effect of yarn fineness on fabric wicking is studied. In order to fulfill the objective, 150 denier micro-denier PET yarns containing 34, 48, 108, 144 and 288 filaments were selected.

Predicting air permeability of multifilament polyester woven fabrics using developed fuzzy logic model

The number of filaments in yarn cross-section, weave density, and weave type are considered the most important factors that affect the property of air permeability of multifilament woven fabrics. Microfilament yarns significantly affect the air permeability property of this type of fabric because of the low porosity between the filaments. This study deals with the development of a fuzzy logic model for predicting the air permeability of multifilament polyester woven fabrics produced from conventional and microfilament yarns. The polyester multifilament yarns used in this study were produced with three different microfilament fineness and two conventional filament fineness levels. The woven fabric samples used in this study were obtained in three weave types: plain, twill, and satin, and with five different weave densities. In accordance with the experimental test results, both regression analysis and fuzzy logic system were built. The air permeability results generated from the developed fuzzy model and the regression equations were compared with the experimental values. Satisfactory and accurate prediction results were obtained with the developed fuzzy logic model. The mean absolute error of the fuzzy model and regression analysis were found to be 2.32%, 12.59%, respectively. Therefore, it was confirmed that the fuzzy model was superior in predicting air permeability.

A comparative study on performance characteristics of multicomponent core-spun yarns containing cotton/PET/elastane

This paper experimentally investigated the characteristics of different (filament and multicomponent) core-spun yarn type. Filament core-spun yarns comprised cotton covered drawn textured (DTY) polyester (PET) filaments with four different filament finenesses. Regarding the production of multicomponent (dual) core-spun yarns, both PET with four different filament finenesses and elastane with four levels of draft variable were fed simultaneously. Yarn samples were produced with modified ring spinning system at the same spinning conditions. As a control group, 100% cotton ring-spun yarn was also manufactured. Tensile properties, unevenness, imperfections and hairiness of yarn samples were determined. Also, fatigue characteristics of yarn samples were examined at two different loading of cycles. The results showed that filament fineness had a significant effect on all yarn properties being determined. Dynamic modulus and dynamic strain properties of yarns, filament fineness, elastane draft and number of cycle were found to be statistically significant at 0.05 level.

Porosity and air permeability relationship of denim fabrics produced using core-spun yarns with different filament finenesses for filling

In this article, porosity and air permeability of denim fabric produced from filament core-spun yarns with different filament fineness and yarn linear density were demonstrated. For this purpose, 110 dtex drawn textured polyester filaments with conventional, fine, and micro finenesses were used as core part, and combed cotton fiber was used as sheath part to obtain core-spun yarns with four different yarn linear density on a modified ring spinning system with the same spinning parameters. Besides the production of core-spun yarns, 100% cotton ring-spun yarns were produced as control group at the same conditions for each yarn linear density, as well. To evaluate the effect of filament fineness and yarn linear density on air permeability and total porosity, denim fabrics were obtained by using 24 yarn samples as weft at the same cover factor with four determined weft densities. Results showed that filament fineness and yarn linear density have a significant effect on total porosity and air permeability at a significance level of 0.05. In addition, high correlation (79.4%) between air permeability and total porosity of denim fabric samples was observed at a significance level of 0.01.

A Research on the Use of Copper Core Yarns in Electromagnetic Shielding Application

In this work, possibilities for producing textile materials with copper core cotton yarns for the purpose of electromagnetic shielding were studied. Cu/Co core yarns were produced by using copper filaments as core material with two different diameters (0.05 and 0.07mm) and cotton as sheath material. All core yarns are produced in Ne 8 yarn count. Conductive Cu/Co yarns were integrated in to 3/1 twill woven fabric structure in the weft direction with 5 different weft densities (8, 13, 18, 23 and 28 per cm). According to the TS EN 50147-1 standard, the shielding effectiveness of these fabrics was measured in the frequency range 1 GHz - 6 GHz. The results have shown that EMSE of fabrics can be tailored by changing the weft density, core filament fineness and wave frequency parameters.

New Image Analysis Method for Determination of the Inter-Fibre Pore Size Intensity of Polyester Woven Barrier Fabrics

Porosity is an important characteristic of a filter textile, which affects permeability and retention properties. Determination of the inter-yarn and inter-fibre pore sizes of barrier textiles is also required to assess the filter behaviour of these textiles. In this study, a software tool was developed to detect the inter-fibre pore size distribution and pore size intensity of multifilament woven barrier fabrics using cross-section images. Fabrics were chosen according to their fabric construction parameters, such as the fabric index, weft yarn filament fineness and weft yarn structure (flat or textured). Microscopic cross-section images of weft yarns were taken, processed to binary images, and analysed with respect to the pore size distribution, number of pore lengths and pore intensity. It was also analysed how the fabric index, filament cross-section and filament fineness affect the inter-fibre pore lengths and separation level proposed. It was found that weft yarns with wider lengths and lower height showed wider inter-fibre pores. Inter-fibre pores decreased with a decrease in filament fineness. Moreover the separation level proposed deviated from the 90% level depending on the fabric index. This deviation was very small in samples with reduced filament fineness and textured samples. The separation level proposed will be useful to understand the effect of fabric construction parameters to obtain targeted properties regarding inter-fibre and inter-yarn pore size.

Effect of Filament Fineness on Composite Yarn Residual Torque

Abstract Yarn residual torque or twist liveliness occurs when the twist is imparted to spin the fibers during yarn formation. It causes yarn snarling, which is an undesirable property and can lead the problems for further processes such as weaving and knitting. It affects the spirality of knitted fabrics and skewness of woven fabrics. Generally, yarn residual torque depends on yarn twist, yarn linear density, and fiber properties used. Composite yarns are widely produced to exploit two yarns with different properties such on optimum way at the same time and these yarns can be produced by wrapping sheath fibers around filament core fiber with a certain twist. In this study, the effect of filament fineness used as core component of composite yarn on residual torque was analyzed. Thus, the false twist textured polyester filament yarns with different filament fineness were used to produce composite yarns with different yarn count. The variance analysis was performed to determine the significance of twist liveliness of filament yarns and yarn count on yarn twist liveliness. Results showed that there is a statistically significant differences at significance level of α=0.05 between filament fineness and yarn residual torque of composite yarns.

Electromagnetic absorption behaviour of carbon helical/coiled yarn woven and knitted fabrics and their composites

In this study, a novel carbon helical/coiled yarn was prepared for developing an electromagnetic (EM) absorbing structure in C-band region (4–8 GHz). The carbon helical yarn was fabricated in a direct twisting machine in which a stainless steel (SS) filament was used as the core and carbon yarn was used as the wrapping thread. The woven and plain knit structures were prepared using the carbon helical yarns. Subsequently, composites were prepared by film stacking method by sandwiching a helical yarn fabric between the polypropylene films. The shielding behaviour of fabrics and the composites was tested using the waveguide method. It was observed that 1/1 plain knit fabric having an optimum number of core SS filaments and helical yarn density of 50–150 turns/m showed a higher absorption coefficient of 0.91 than other fabrics. Hence, a particular proportion of helical carbon and SS content in a fabric maximizes its absorption coefficient. In the composite form, the absorption level was reduced and behaved like a metal. In addition, increase in fineness of core SS filaments also decreased the absorption behaviour of fabrics and composites. However, the overall shielding effectiveness of fabric and composite was increased for increasing the wrapping density. Compared to fabric form, composites showed larger reflective and total loss. In addition, three-point flexural strength and impact energy absorption of helical yarn composites were also investigated. The developed fabrics can be used as EM absorbing structures in domestic and military applications, whereas the composite can be used as shielding panels to the replacement of metal shield.

Prediction of yarn crimp in PES multifilament woven barrier fabrics using artificial neural network

This research was aimed to develop artificial neural network (ANN) models to predict yarn crimp in woven barrier fabrics. For ANN training, 52 polyester (PES) multifilament barrier fabrics were produced by varying weft yarn and filament fineness, yarn type, weft density, weave type, and loom parameters. The supervised training of neural network was performed using Matlab® ANN toolbox function ‘trainbr’ which is the incorporation of Levenberg-Marquardt (LM) optimization and automated Bayesian regularization into backpropagation. From modeling outcomes, it was observed that both warp and weft yarn crimp models have generalized well with excellent coefficient of determination and trivial mean absolute error when tested on novel data. Moreover, input rank analysis of optimized network provided important information about model stability with respect to input variables, and trend analysis elucidated the input-crimp behavior using different input levels.

Fatigue behaviour of core-spun yarns containing filament by means of cyclic dynamic loading

The behaviour of yarns under dynamic loading is important that leads to understand the growth characteristics which is exposed to repetitive loadings during usage of fabric made from these yarns. Fabric growth is undesirable property that originated from low resilience characteristics of fabric. In this study, the effects of the filament fineness and yarn linear density on fatigue behaviour of rigid-core spun yarns were determined. Cotton covered yarns containing different filament fineness of polyester (PET) draw textured yarns (DTY) (100d/36f, 100d/96f, 100d/144f, 100d/192f and 100d/333f) and yarn linear densities (37 tex, 30 tex, 25 tex and 21 tex) were manufactured by using a modified ring spinning system at the same spinning parameters. Repetitive loads were applied for 25 cycles at levels between 0.1 and 3 N. Dynamic modulus and dynamic strain of yarn samples were analyzed statistically. Results showed that filament fineness and yarn linear density have significance effect on dynamic modulus and dynamic strain after cyclic loading.

A Comparative Strength Analysis of Denim Fabrics Made from Core-Spun Yarns Containing Textured Microfilaments

Denim fabric is one of the most popular casual wear fabrics worldwide. The performance characteristics of denim fabrics have been improved by using functional fibers and elastane to make them comfortable to wear. Elastane fibers with high elasticity are used extensively in denim fabric production. Elastane fibers are generally used as the core part of the core-spun yarns as weft yarns. Besides elastane fibers; polyester and polyester derivatives are commonly used. This study examines the effects of filament fineness and yarn count on denim fabric performance. Textured polyester filaments with medium, fine and micro linear densities were used as the core part of the core-spun yarn and cotton fiber was used as sheath material. Yarn samples manufactured with the same production parameters at different yarn count were used as weft yarns of denim fabrics. Denim fabrics were produced with the same fabric cover factor to eliminate yarn count difference effects. Tensile, static tearing and dynamic tearing properties of denim fabrics were determined. To evaluate the effects of core part, 100 % cotton denim fabric was manufactured and tested. Statistical analysis was performed to analyze the significance of filament fineness and yarn count ratio. Results showed that there was a significant effect of filament fineness on tensile, static tearing and dynamic tearing properties of denim fabrics. In addition, it was found that yarn count had no significance effect on static tearing properties of denim fabrics.

Development and comparison of artificial neural network and statistical model for prediction of thermo-physiological properties of polyester–cotton plated fabrics

AbstractThermo-physiological properties of textiles play a very crucial role in providing thermal equilibrium to human beings in changing ambient conditions and activity level and in turn dictate the overall wearer comfort. A number of prediction tools like mechanistic, statistical and stochastic (artificial neural network) models are finding application in textiles for reasonable prediction of various aspects of textiles before the actual commencement of fabric production and testing. In this study, thermo-physiological properties of polyester–cotton plated fabrics were predicted by two approaches: artificial neural network and response surface equations. A multilayered back propagation artificial neural network was developed with four input nodes corresponding to four selected input parameters: back layer yarn linear density, filament fineness, total yarn linear density and loop length and one output node corresponding to the predicted thermo-physiological property. Four individual networks working in tandem with common set of input parameters and each giving an individual output were developed such that the outputs of four networks were thermal resistance, thermal absorptivity, air permeability and moisture vapour transmission rate respectively. Network architecture gave good prediction performance with low values of mean absolute percentage error and high coefficient of determination. Response surface equations were developed to predict the thermo-physiological properties and good agreement between experimental and predicted values for all the properties was found with coefficient of determination over 0.9. Artificial neural network predicted the thermal resistance and air permeability of plated fabrics with good accuracy. However, the response surface equations served better prediction tool for thermal absorptivity and moisture vapour transmission rate prediction.