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1 – 10 of 148Saba Sareminia, Zahra Ghayoumian and Fatemeh Haghighat
The textile industry holds immense significance in the economy of any nation, particularly in the production of synthetic yarn and fabrics. Consequently, the pursuit of acquiring…
Abstract
Purpose
The textile industry holds immense significance in the economy of any nation, particularly in the production of synthetic yarn and fabrics. Consequently, the pursuit of acquiring high-quality products at a reduced cost has become a significant concern for countries. The primary objective of this research is to leverage data mining and data intelligence techniques to enhance and refine the production process of texturized yarn by developing an intelligent operating guide that enables the adjustment of production process parameters in the texturized yarn manufacturing process, based on the specifications of raw materials.
Design/methodology/approach
This research undertook a systematic literature review to explore the various factors that influence yarn quality. Data mining techniques, including deep learning, K-nearest neighbor (KNN), decision tree, Naïve Bayes, support vector machine and VOTE, were employed to identify the most crucial factors. Subsequently, an executive and dynamic guide was developed utilizing data intelligence tools such as Power BI (Business Intelligence). The proposed model was then applied to the production process of a textile company in Iran 2020 to 2021.
Findings
The results of this research highlight that the production process parameters exert a more significant influence on texturized yarn quality than the characteristics of raw materials. The executive production guide was designed by selecting the optimal combination of production process parameters, namely draw ratio, D/Y and primary temperature, with the incorporation of limiting indexes derived from the raw material characteristics to predict tenacity and elongation.
Originality/value
This paper contributes by introducing a novel method for creating a dynamic guide. An intelligent and dynamic guide for tenacity and elongation in texturized yarn production was proposed, boasting an approximate accuracy rate of 80%. This developed guide is dynamic and seamlessly integrated with the production database. It undergoes regular updates every three months, incorporating the selected features of the process and raw materials, their respective thresholds, and the predicted levels of elongation and tenacity.
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Georgy Sunny and T. Palani Rajan
The purpose of the study is to optimize the blending ratio of Arecanut and cotton fibers to create yarn with the best quality for various applications, particularly home…
Abstract
Purpose
The purpose of the study is to optimize the blending ratio of Arecanut and cotton fibers to create yarn with the best quality for various applications, particularly home furnishings. The study aims to determine the effect of different blend ratios on the physical and mechanical properties of the yarn.
Design/methodology/approach
The study involves blending Arecanut and cotton fibers in various ratios (90:10, 75:25, 50:50, 25:75 and 10:90) at two different yarn counts (10/1 and 5/1). Various physical and mechanical properties of the blended yarn are analyzed, including unevenness, coefficient of mass variation (cvm%), imperfection, hairiness, breaking strength, elongation, tenacity and breaking work.
Findings
The research findings suggest that the blend ratio of 10:90 (10% cotton and 90% Arecanut fiber) produced the best results in terms of physical and mechanical properties for both yarn counts. This blend ratio resulted in reduced unevenness, cvm% and imperfection, while also exhibiting good mechanical properties such as breaking strength, elongation, tenacity and breaking work. The blend with a higher concentration of cotton generally showed better properties due to the coarseness of Arecanut fiber. As the goal of the study was to determine the best blend ratio that included the most Arecanut fiber based on its physical and mechanical properties, which is suitable for home furnishing applications, 75:25 Areca cotton blend ratio of yarn count 5/1 proved to be the best.
Research limitations/implications
The study acknowledges that Arecanut fiber must be blended with other commercially used fibers like cotton due to its coarseness. While the study provides insights into optimizing blend ratios for home furnishings and packaging, further research may be needed to make the material suitable for clothing applications.
Practical implications
The research has practical implications for industries interested in utilizing Arecanut and cotton blends for various applications, such as home furnishings and packaging materials. It suggests that specific blend ratios can result in yarn with desirable properties for these purposes.
Social implications
The study mentions that the increased use of Arecanut fibers can benefit the growers of Arecanut, potentially providing economic opportunities for communities engaged in Arecanut farming.
Originality/value
The research explores the utilization of Arecanut fibers, an underutilized resource, in combination with cotton to create sustainable yarn. It assesses various blend ratios and their impact on yarn properties, contributing to the understanding of eco-friendly textile materials.
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Yunchu Yang, Hengyu Wang, Hangyu Yan, Yunfeng Ni and Jinyu Li
The heat transfer properties play significant roles in the thermal comfort of the clothing products. The purpose of this paper is to find the relationship between heat transfer…
Abstract
Purpose
The heat transfer properties play significant roles in the thermal comfort of the clothing products. The purpose of this paper is to find the relationship between heat transfer properties and fabrics' structure, yarn properties and predict the effective thermal conductivity of single layer woven fabrics by a parametric mathematical model.
Design/methodology/approach
First, the weave unit was divided into four types of element regions, including yarn overlap regions, yarn crossing regions, yarn floating regions and pore regions. Second, the number and area proportion of each region were calculated respectively. Some formulas were created to calculate the effective thermal conductivity of each element region based on serial model, parallel model or series–parallel mixing model. Finally, according to the number and area proportion of each region in weave unit, the formulas were established to calculate the fabric overall effective thermal conductivity in thickness direction based on the parallel models.
Findings
The influences of yarn spacing, yarn width, fabric thickness, the compressing coefficients of air layers and weave type on the effective thermal conductivity were further discussed respectively. In this model, the relationships between the effective thermal conductivity and each parameter are some polynomial fitting curves with different orders. Weave type affects the change of effective thermal conductivity mainly through the numbers of different elements and their area ratios.
Originality/value
In this model, the formulas were created respectively to calculate the effective thermal conductivity of each element region and whole weave unit. The serial–parallel mixing characteristics of yarn and surrounding air are considered, as well as the compression coefficients of air layers. The results of this study can be further applied to the optimal design of mixture fabrics with different warp and filling yarn densities or different yarn thermal properties.
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Fei Sun, Haisang Liu, Yuqin Din, Honglian Cong and Zhijia Dong
The purpose of this research is to propose a flexible sensor with a weft-knitted float stitch structure and to explore knitting techniques that allow conductive yarns to be…
Abstract
Purpose
The purpose of this research is to propose a flexible sensor with a weft-knitted float stitch structure and to explore knitting techniques that allow conductive yarns to be skin-tight and less exposed, reducing production processes and increasing productivity. Study its electrical conductivity in different yarn materials, knit processes and deformation ranges. The analysis is compared to provide some basis for the design of the electrodes.
Design/methodology/approach
The method includes five operations: (1) Analysis of the morphological appearance, tensile variation, fiber material properties and electrical conductivity of high-elastic and filament silver-plated conductive yarns. (2) Based on the knitting process of the floating yarn structure, three-dimensional modeling of the flexible sensor was carried out to explore the influence of knitting process changes on appearance characteristics. (3) The fabric samples are knitted by different silver-plated conductive yarns with different structures. Processing of experimental samples to finished size by advance shrinkage. (4) Measure the resistance of the experimental sample after the machine has been lowered and after pre-shrinking. Use the stretching machine to simulate a wearing experiment and measure the change in resistance of the sample in the 0–15% stretching range. (5) Analyze the influence factors on the conductive performance of the flexible sensor to determine whether it is suitable for textile flexible sensors.
Findings
For the float knitted flexible sensors, the floating wire projection is influenced by the elasticity of the fabric and the length of the floating wire. Compared to the plain knitted flexible sensors, it has less resistance variation and better electrical properties, making it suitable for making electrodes for textile structures. In addition, the knitting method is integrated with the intelligent monitoring clothing, which saves the process for the integration of the flexible sensor, realizes positioning and fixed-point knitting.
Practical implications
The sensor technology of the designed weft-knitted float structure is varied and can be freely combined and designed in a wide range. Within the good electrical conductivity, the flexible sensor can realize integrated knitting, positioning monitoring, integrating into the appearance of clothing. It can also focus on the wearing experience of wearable products so that the appearance of the monitoring clothing is close to the clothes we wear in our daily life.
Originality/value
In this paper, an integrated positioning knitting flexible sensor based on the weft knitting float structure is studied. The improved knitting process allows the sensing contact surface to be close to the skin and reduces the integration process. The relationship between the exposure of the silver-plated yarn on the clothing surface and the electrical conductivity is analyzed. Within a certain conductive performance, reduces the exposed area of the conductive yarn on the clothing surface and proposes a design reference for the flexible sensor appearance.
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Toshit Jain, Jinesh Kumar Jain, Rajeev Agrawal and Shubha Johri
Environmental impact and changes are becoming essential in textile and yarn industries, where reliable measurement of parameters related to processing harmful substances needs to…
Abstract
Purpose
Environmental impact and changes are becoming essential in textile and yarn industries, where reliable measurement of parameters related to processing harmful substances needs to be examined. Such findings can be cumulated using smart assessment like life cycle analysis. The ecological impact category, supply chain, and climate-changing factors were considered for the necessary assessment.
Design/methodology/approach
This paper applies the Life Cycle Assessment technique in the textile and yarn industry to estimate critical environmental potentials. The critical input for the fabric and yarn industry was put in the GaBi software model to estimate various environmental potentials.
Findings
Global warming potential, electricity, and raw cotton consumption in the fabric and yarn industry were critical concerns where attention should be focused on minimizing environmental potentials from cradle to gate assessment.
Research limitations/implications
This qualitative study is made via the industry case-wise inputs and outputs, which can vary with demographic conditions. Some machine and human constraints have not been implemented in modelling life cycle model for smart simulation. Smart simulation helps in linking different parameters and simulates their combined effects on the product life cycle.
Practical implications
This modelling approach will help access pollution constituents in different supply chain production processes and optimize them simultaneously.
Originality/value
The raw data used in this analysis are collected from an Indian small scale textile industry. In the textile fabrication industry, earlier assessments were carried out in cotton generation, impact of PET, cradle to grave assessment of textile products and garment processing only. In this research the smart model is drawn to consider each input parameter of yarn and textile fabric to determine the criticality of each input in this assessment. This article mainly talks about life cycle and circular supply assessment applied to first time for both cotton to yarn processing and yarn to fabric industry for necessary estimation of environment potentials.
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Sheraz Hussain Siddique Hussain Yousfani, Salma Farooq, Quratulain Mohtashim and Hugh Gong
Porosity is one of the most important properties of the textile substrate. It can influence the comfort of a garment by affecting its breathability and thermal conductivity…
Abstract
Purpose
Porosity is one of the most important properties of the textile substrate. It can influence the comfort of a garment by affecting its breathability and thermal conductivity. During the process of dyeing, the dye liquor comes in contact with the substrate; the absorption of the dye liquor into the substrate will be dependent on its porosity. The concept of porosity between the yarns of fabric is a common phenomenon; however, the porosity between the fibres in the yarn can also influence the dyeing behaviour of the fabric.
Design/methodology/approach
In this research, ring and rotor yarns of 25/s and 30/s counts are considered as textile substrates. The porosity of yarns was determined theoretically and experimentally using the image analysis method.
Findings
It was found that theoretical porosity is independent of the yarn manufacturing method. In addition, 30/s yarn was more porous as compared with 25/s yarn having a higher pore area. Rotor yarns had higher porosity, dye fixation and K/S as compared with ring yarns. Dyeing behaviour was also dependent on the count of yarn. Specifically, 30/s yarns have higher dye fixation as compared with 25/s yarns. However, 25/s yarns were dyed with deeper shades showing higher K/S values. Also, 25/s yarns are coarser than 30/s yarns having higher diameters and cross-sectional area, thus resulting in deeper shades and higher K/S values.
Originality/value
This novel technique is based on the comparative study of the porosity of various types of yarns using the image analysis technique. This investigation shows that the porosity between the fibres in the yarn can also influence the dyeing behaviour of the yarn.
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Xiaoyan Wang, Jiaxin Zhang, Yang Jiang, Jinmei Du, Dagang Miao and Changhai Xu
This paper aims to determine the most practically applicable color-difference formula for yarn-dyed fabrics woven from warp and weft yarns in different color depths and to…
Abstract
Purpose
This paper aims to determine the most practically applicable color-difference formula for yarn-dyed fabrics woven from warp and weft yarns in different color depths and to establish color-difference tolerance for perceptibility by evaluating yarn-dyed fabrics visually and instrumentally.
Design/methodology/approach
A total of 108 sample pairs were evaluated by a panel of 13 observers with perceptibility method under three typical light sources (A, D65 and cool white fluorescent). The data sets were statistically analyzed by the homogeneity of variance test (F-test), analysis of variance, standardized residual sum of squares and performance factor/3.
Findings
Light sources had a slight influence on the visual assessments of yarn-dyed fabrics. Among the eight color-difference formulae for measurements of yarn-dyed fabrics, CIEDE2000(2:1:1) outperformed all other tested formulae, and the color tolerance for the perceptibility of CIEDE2000(2:1:1) was 0.62. When the homochromy index (K) of warp and weft yarns of yarn-dyed fabric was lower than 1.25, the color difference based on ΔE*00(2:1:1) between the two samples was acceptable in terms of the color tolerance for perceptibility (i.e. 0.62).
Practical implications
The warp and weft yarns in different color depths could be woven in fabric with a relatively uniform color appearance.
Originality/value
This study could contribute to cost savings by reusing disqualified dyed yarns during the weaving manufacturing process.
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Abenezer Fikre Hailemariam and Nuredin Muhammed
The purpose of this study is to investigate the mechanical properties of denim fabrics constructed from ring-spun and open-end rotor spun yarns.
Abstract
Purpose
The purpose of this study is to investigate the mechanical properties of denim fabrics constructed from ring-spun and open-end rotor spun yarns.
Design/methodology/approach
Yarns of 10s Ne count using cotton fibers were spun using the ring and open-end rotor spinning technologies. The yarns were used to produce a denim fabric on an air-jet loom with a 3/1 twill weave structure. Mechanical tests – tensile strength, tear strength, abrasion resistance and pilling resistance – of denim fabrics were evaluated. The test results were analyzed using analysis of variance with the help of Software Package for Social Sciences.
Findings
Denim fabrics made by using ring-spun yarns exhibited better tensile and tear strength properties than denim fabrics made by using open-end rotor spun yarns. On the contrary, denim produced using open-end rotor yarns have better abrasion resistance, pilling resistance and air permeability than those produced using ring-spun yarns.
Originality/value
Both spinning techniques have a significant influence on the properties of denim fabrics. Whenever better tensile and tear strength is required, it is better to use ring-spun yarns, while if the requirement is better abrasion resistance and pilling resistance with high air permeability, then open-end rotor spun yarns shall be used.
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Hooman Imani, Kamaladin Gharanjig and Zahra Ahmadi
The purpose of this study is simultaneous dyeing and mordanting of wool yarns with extracted cochineal dye and aluminum sulfate to the reduction of consuming energy, water and…
Abstract
Purpose
The purpose of this study is simultaneous dyeing and mordanting of wool yarns with extracted cochineal dye and aluminum sulfate to the reduction of consuming energy, water and time.
Design/methodology/approach
The dyeing process was optimized using the response surface methodology (RSM) approach. pH, dyeing duration and the presence of additives were chosen as variables and the color strength of samples as a response. The color characteristics and fastness attributes of samples dyed in the best condition were evaluated and compared to pre-mordant dyeing outcomes on wool yarns.
Findings
The best conditions for deep dyeing wool with cochineal dye were as follows: pH 2.5, time 110 min and the ratio of aluminum: additives 1:0 at 100 °C. Color strength of dyed wool yarns by one-bath and pre-mordant dyeing methods were approximately the same. Wool yarns can dye to the on-bath dyeing method such that the dyed samples have similar color strength and fastness properties to pre-mordant dyeing.
Social implications
Wool dyeing processes that use one-bath dyeing consume less water and produce fewer effluents. As a result, this strategy conserves water and energy for a higher quality of life. The findings of this study, in general, aid environmental protection.
Originality/value
A novel one-bath process for dyeing wool with cochineal dye at heavy depths is introduced. RSM was used to optimize the procedure and determine effective parameters on the color strength of dyed wools. Using extracted cochineal dye and aluminum sulfate in a simultaneous dyeing technique, good color fastness qualities on wool fibers were achieved.
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Muhammad Umair, Muhammad Usman Javaid, Yasir Nawab, Madeha Jabbar, Shagufta Riaz, Hafiz Affan Abid and Khubab Shaker
This paper aims to investigate the influence of picking sequence, weave design and weft yarn material on the thermal conductivity of the woven fabrics.
Abstract
Purpose
This paper aims to investigate the influence of picking sequence, weave design and weft yarn material on the thermal conductivity of the woven fabrics.
Design/methodology/approach
This work includes the development of 36 woven samples with two weave designs (1/1 plain and 3/1 twill), three picking sequences (single, double and three pick insertion) and six different weft yarn materials (cotton, polyester having 48 filaments, polyester with 144 filaments, spun coolmax having Lycra in core and coolmax in sheath, filament coolmax and polypropylene). The thermal conductivity was measured using ALAMBETA tester.
Findings
The results showed that weft yarn material, weave design and picking sequence have a meaningful impact on the thermal conductivity of woven fabric. The value of thermal conductivity was lowest for the fabrics with three pick insertion and 3/1 twill weave in all weft yarn materials.
Research limitations/implications
Plain woven fabric with single pick insertion is feasible for summer wear to enhance the comfort of wearer. By changing the warp yarn grouping and material, improved thermal conductivity/resistance can also be achieved.
Originality/value
The authors have studied the combined effect of different weft yarn materials with different picking sequences and different weave designs on thermal conductivity of the woven fabrics.
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