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International Journal of Clothing Science and Technology
Journal Prestige (SJR): 0.318  Citation Impact (citeScore): 1 Number of Followers: 4  Hybrid journal * Containing 1  Open Access article(s) in this issue *ISSN (Print) 0955-6222 - ISSN (Online) 1758-5953 Published by Emerald  [362 journals]
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- Examination of the properties of sustainable yarns with Ecocell fiber and
bast fibers in comparison with conventional cotton yarn and organic cotton
yarn-
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Authors: Seval Uyanık, Tulin Kaya Nacarkahya
Abstract: As the use of sustainable raw materials gained importance, the use of natural and regenerated fibers in textiles began to come to the fore and a regenerated plant fiber, which is lyocell fiber and produced in Turkey under the name EcocellTM, formed the basis of this study. The aim of the study was to determine the properties of EcocellTM yarn and blended yarns with EcocellTM as the main fiber and bast fibers, which are linen, recycled linen and hemp, as the second fiber and then to compare them with each other and with conventional cotton and organic cotton yarns, and additionally with the standard yarns given in USTER 2023 Statistics, and most importantly, to reveal the yarn quality, economic and sustainability properties, which yarns can be used instead and the final usage area. In this study, EcocellTM, which is a generic lyocell fiber as the main fiber and linen, recycled linen and hemp as the second fiber were used to produce blended yarns. Conventional cotton fiber and organic cotton fiber were also added for comparison with Ecocell yarn and other blended yarns. All yarns are produced in two yarn counts, Ne 24 and Ne 28, in the ring spinning system. The component determination processes of the used fibers were carried out in five steps. After, Fourier Transform Infrared (FTIR) analysis to determine the functional groups and determination of the physical and performance properties of the yarns were performed. Lastly, the properties of obtained yarns were compared with the properties of standard yarns given in USTER 2023 Statistics. EcocellTM fiber contributes positively to yarn properties, reducing unevenness and yarn imperfections, improving tensile properties by increasing breaking strength and elongation values and reducing the yarn-metal friction coefficient, but increasing yarn hairiness by having a negative effect due to fibrillation. Positive contribution of bast fibers was only in the yarn tensile properties due to their high fiber strength and elongation, and they especially hemp fiber significantly increased yarn unevenness and imperfection since they are thicker and have higher length variations. The content of lignin negatively affected the yarn friction coefficient. When blended with bast fibers, Ecocell yarns were negatively affected. Raw material selection in textiles has become much more important regarding sustainability. Sustainable regenerated cellulosic fibers also gained importance in this context, and lyocell fiber began to be produced in Turkey with the trade name Ecocell. In this study, it was found that although it does not meet expectations economically and is much more expensive than standard yarns, EcocellTM yarn and EcocellTM yarn with 10% bast fibers are much more advantageous in terms of sustainability, especially than cotton, flax, viscose and modal yarns, and considering yarn quality, it is also better than most standard yarns. Only regarding yarn quality, these yarns can also be used instead of polyester, acrylic or organic cotton, which are more sustainable yarns according to the Higg MSI index.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-03-27
DOI: 10.1108/IJCST-01-2024-0021
Issue No: Vol. ahead-of-print, No. ahead-of-print (2025)
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- Study on the pressure comfort of elbow guards for older women based on
numerical analysis and experimental methods-
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Authors: Ke-Ke Sun, Tian-tian Xu, Yin-hong Yao, Miao-miao Kang
Abstract: This study aims to provide three biomechanical models that are consistent with the arm forces of elderly women and to design elbow guards that are more suitable for their use. Numerical analysis and experimental methods were used to determine the optimal direction for elbow guard design, focusing on fabric type, arm force distribution and comfort thresholds. This paper explores the design of elbow guards for older women through predictive finite element modeling and a systematic experimental approach. First, contact anthropometry was used to measure the arm dimensions of older women. Cluster analysis was applied to categorize arm sizes, laying the foundation for the subsequent selection of subjects for 3D scanning. Second, a 3D scanner was used to obtain the external contours of a representative subject’s arm. Finite element models of the arm and elbow guard were constructed with the arm flexed at three different angles. These models were used to simulate the pressure exerted by the elbow guard on the arm. Next, objective measurements of garment pressure were taken using a homemade elbow guard. Finally, subjective comfort evaluation was carried out using the human clothing experiment method. Comfortable pressure thresholds were determined by establishing a correlation between subjective comfort levels and objective pressure values. The results showed that the developed model effectively predicted the pressure distribution between the elbow guard and the arm. By comparing the simulated pressure distributions of the four materials, it was determined that polyamide and spandex fabrics were the more appropriate materials for the elbow pad design. Additionally, the study pointed out the need to consider the different bending postures of the arm when analyzing pressure, focusing on the amount of pressure control at the elbow of the arm. When the arm’s bending angle ranges between 90° and 180°, the total pressure should remain between a minimum of 2550.0 Pa and a maximum of 4394.4 Pa. The theoretical approach of ellipses was used to construct the arm model. Numerical simulations were performed to analyze the pressure distribution for three different arm bending postures, and the simulation results provided useful insights for designers in selecting the optimal fabric type. This study provides a theoretical reference for designing comfortable compression elbow guards, while also addressing garment comfort by establishing accurate garment comfort thresholds to guide designers in understanding the appropriate compression dosage. (1)The theory related to ellipses is introduced in the construction of the model, unlike other studies.(2)The laws of fabric material, force area and bending angle on pressure distribution were analyzed.(3)Clothing pressure comfort thresholds were determined for three different postures.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-03-19
DOI: 10.1108/IJCST-05-2024-0111
Issue No: Vol. ahead-of-print, No. ahead-of-print (2025)
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- Fashion-tile: a tiled clothing image generation model based on improved
conditional generative adversarial network-
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Authors: Meihua Gu, Yalu Chu, Xiaoxiao Dong
Abstract: Clothing retrieval and matching tasks require the use of model clothing images as input. Due to the limitation of shooting postures and angles, direct using of model images for clothing retrieval or matching often faces many challenges. In view of this, this paper aims to propose a novel tiled clothing image generation model based on improved conditional generative adversarial network (GAN) that can generate clear and accurate tiled clothing images from selected model images. Aiming at the problems of local information loss and overall structure inaccuracy in tile clothing image generation, this paper optimizes pix2pixHD network model from three aspects: using spatial transformer network (STN) for spatial invariance optimization, using atrous spatial pyramid pooling (ASPP) for feature extraction optimization, using self-attention (SA) for global context information acquisition optimization. The improved network model is called fashion-tile, which can improve the quality and fidelity of tile clothing image generation. The experimental results show that the proposed method is obviously superior to the existing methods not only in the evaluation metrics, but also in the generating clothing image quality and fidelity. The peak signal-to-noise ratio (PSNR) value is increased by at least 6.6%, the structural similarity (SSIM) value is increased by at least 2.1%, and the Fréchet inception distance (FID) value is reduced by at least 8.6% on the person2cloth dataset. This work generates high-quality tiled clothing images that enhance the preservation of clothing details and structures, providing consumers with a clearer and more realistic visual experience, thereby increasing shopping satisfaction and purchase intention. With continuous technological advancements and deeper application, the proposed method is expected to play a greater role in the future of clothing e-commerce, offering consumers a richer and more authentic shopping experience. The proposed method provides an effective solution for generating tiled clothing from model images, which will help to improve the accuracy of subsequent clothing retrieval and matching, and help to enhance the consumers shopping experience and effectively promote sales.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-03-17
DOI: 10.1108/IJCST-05-2024-0115
Issue No: Vol. ahead-of-print, No. ahead-of-print (2025)
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- Exploring the dyeability and sustainability of lac dye on cotton:
a comparative analysis between water and supercritical CO dyeing-
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Authors: Christiana Agbo, Satoko Okubayashi
Abstract: The textile industry has been seeking sustainable dyeing methods to minimize environmental impact. This study addresses this need by assessing the use of supercritical carbon dioxide (scCO2) dyeing for applying lac dye to cotton fabrics. A comparison with the water dyeing method was made with the primary objective of evaluating the dyeing performance. Dyeing of cotton with lac dye was carried out by water dyeing and the supercritical carbon dioxide (scCO2) dyeing methods incorporating pretreatments and mordanting such as polyethylene glycol 400 (PEG), aluminum acetate (A.A), tannic acid (T.A) and benzamide. The dyeing performance of lac dye on cotton fabrics for both methods as well as mechanical properties were evaluated. This study showed differences in color yield, fastness properties and dyeing efficiency between both methods. Supercritical CO2 showed significantly higher color strength (K/S), uniformity and fastness properties to water dyeing. The K/S values of the water-dyed samples were between 1.10 and 1.76. However, the K/S of scCO2 dyed samples increased from 0.85 to 4.26 when pre-treated with PEG. Also, the use of Aluminum Acetate (A.A) as a mordant gave the highest K/S of 6.35. The dyeing of natural fibers, especially cotton, has faced difficulties, especially with the use of natural dyes. In this study, the use of mordants in the dyeing process aids in improving the dyeability of cotton, especially in scCO2 dyeing. This study compares traditional aqueous and scCO2 dyeing methods for lac dye on cotton, focusing on sustainability and dyeability.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-03-13
DOI: 10.1108/IJCST-05-2024-0113
Issue No: Vol. ahead-of-print, No. ahead-of-print (2025)
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- Influence of sports bra parameters on vertical breast movement using
three-dimensional-printed manikin evaluation method-
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Authors: Mingjie Wu, Lian Zeng, Haiyu Dong, Xiaona Chen, Guangwu Sun
Abstract: Sports bras can effectively reduce breast displacement, alleviate breast pain and protect the breast. Different bra components have different effects on breast support. This study aims to explore the quantitative relationship between bra components and vibration reduction function. To understand the effects of different bra component parameters on breast support, 30 sports bras were fabricated with precise component parameters. The dynamic vertical breast displacement when wearing each sports bra was monitored using motion capture technology. The breast displacement data from five breast positions was used to analyze the overall vertical displacement of the breast. To address variability due to differences in human anatomy, the experiments were conducted on a custom-made manikin prepared using three-dimensional printing. Compared with bare breasts, breasts supported by bras made with high-elastic-modulus cup materials, high-elastic-modulus shoulder strap materials and polyester underbands exhibited reduced vertical displacement during physical activity. Structurally, bras with higher cup heights, shorter strap lengths and smaller underband circumferences were associated with reduced overall breast displacement during physical activity. By systematically studying the effects of different bra components on breast support, this study provides valuable insight and recommendations for the design and materials selection of sports bras.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-03-13
DOI: 10.1108/IJCST-07-2024-0153
Issue No: Vol. ahead-of-print, No. ahead-of-print (2025)
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- Development of a reference database on historical body sizing and digital
twins-
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Authors: Aleksei Moskvin, Mariia Moskvina, Victor Kuzmichev
Abstract: Historical body sizing systems are widely used in reconstructions to reproduce the shape of the human body. However, the systems are less informative than modern standards. The article aims to present a framework for processing historical sizing systems and to generalize 19th century adult female body sizes within one reference anthropometric database. The study adapted historical data on body sizing to the modern methodology of creating sizing systems. It systematized 248 typical sizes from 33 sources published in North America between 1875 and 1918. The common body measurements were examined by means of correlation analysis. The data was used to introduce new key dimensions and body sizes. Regression models for calculating secondary dimensions were established. A parametric modelling software program was used to generate avatars in accordance with the developed database. The developed database presents 111 typical body sizes divided into five constitution and three height groups. The new database agrees with historical body sizes published in Europe. The differences between the developed database and modern standards were confirmed to be in line with changes in the shape of the body during the 19th and the 20th century. The study provides historical reconstructions and exhibitions with a reliable and comprehensive source of anthropometric data, as well as a diverse range of virtual mannequins.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-03-12
DOI: 10.1108/IJCST-04-2024-0086
Issue No: Vol. ahead-of-print, No. ahead-of-print (2025)
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- Forecasting customer behaviors for new fashion product development:
a decision support system-
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Authors: Nhu Ngoc Phan Ha, Thi Kim Hue Trinh, Song Thanh Quynh Le
Abstract: In the fashion industry, the new product development process is considered as a powerful tool that supports companies to survive and achieve greater success in dynamic markets. This study aims to create a predictive model that utilizes data mining techniques to identify the factors that influence customer behavior and estimate their clothing purchase preferences in this process. This paper first determined the relationship between the product’s material and prices based on customers’ viewpoints through the K-means clustering technique. In the next step, customers’ preferences were measured through these fashion product’s attributes including colors, forms, styles and patterns by Conjoint analysis. By collecting and analyzing data from markets and customers, reliable suggestions were proposed for designing garments that satisfy customers’ demands and raise company profits. These results from the forecasting model could support managers in making the best decisions, being time efficient and saving costs during the new product development process. This study describes a new understanding of the elements influencing consumers’ behavior that are connected to fashion products. The incorporation of market data and scientific knowledge will improve the success of the new product development process.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-03-04
DOI: 10.1108/IJCST-02-2024-0032
Issue No: Vol. ahead-of-print, No. ahead-of-print (2025)
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- Development of garment design system using random polygon pattern
generator-
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Authors: Jihyun Oh, Sungmin Kim
Abstract: This study aims to develop a random polygon garment pattern generator and a drape simulation system to automate the garment design process. Garments were categorized into four groups based on the geometric features of the human body. Garment patterns in each group consisted of basic points, and the patterns were automatically placed, sewn and simulated around the body in three-dimensional space. Additional pattern manipulation functions were developed to modify the shapes of patterns by adding darts and cuts, either manually or randomly. Users can produce new designs they had not considered before using the random manipulation functions. Since the three-dimensional simulation process is automated, users can focus solely on the design process. Garments composed of multiple layers were not considered. This system differs from existing clothing computer-aided design systems in that even users lacking prior knowledge of garment design can generate various examples. It can help users understand the relationship between 2D patterns and 3D garments without the need for a pattern drafting process.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-03-04
DOI: 10.1108/IJCST-05-2024-0104
Issue No: Vol. ahead-of-print, No. ahead-of-print (2025)
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- More sustainable denim fading process of two different indigo dyed denim
fabrics with laser treatment-
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Authors: Tuna Uysaler, Pelin Altay, Gülay Özcan
Abstract: Laser fading, commonly used in the denim industry, is a computer-controlled, dry, ecological finishing method whereas conventional methods include high water, energy and time consumption. Resolution and pixel time are crucial parameters of laser source influencing the effect of laser treatment. The purpose of this study is to determine the optimum laser parameters of CO2 laser followed by enzyme washing and to compare the tensile strength and color values of laser-treated denim fabric with that of conventional enzyme-faded. Two different indigo-dyed, sulfur bottom-indigo-dyed and only indigo-dyed organic cotton denim fabrics with different unit weights, were lasetreated with different laser parameters and then subjected to 10 min enzyme washing. Tensile strength, abrasion resistance, and change in fabric unit weight were tested. CIE (L*a*b*, ΔE*, h°, C*) color values, color strength (K/S), yellowness and whiteness indexes were measured to identify the color differences. Color fastness tests including washing, rubbing, light, water and perspiration fastness were investigated. Most effective laser fading in terms of good mechanical properties and color values was obtained at 40 dpi resolution and 300 µs pixel time. Conventional enzyme fading of denim fabrics is a wet process and requires a long process time of 40–45 min and high temperatures, leading to high energy and water consumption. Laser fading, on the other hand, is a dry and ecological method, but causes a decrease in mechanical properties of the fabric, and an increase in yellowness. In this study, unlike the similar studies in the literature, denim fading was carried out by a combination of laser treatment followed by only 10 min enzyme washing in order to eliminate or minimize the drawbacks of the denim fading, such as high energy and water consumption for enzyme fading and decrease in mechanical properties of the fabric and increase in yellowness for laser fading. This method was applied to two different dyed denim fabrics, sulfur (bottom) and indigo (top) and laser process conditions were optimized to achieve the desired fading effects compared to conventional enzyme fading.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-02-11
DOI: 10.1108/IJCST-05-2024-0117
Issue No: Vol. ahead-of-print, No. ahead-of-print (2025)
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- Development of functional jackets for reducing workload and
boosting muscle strength-
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Authors: Sunhee Park, Yejin Lee
Abstract: This study evaluated the effect of functional jackets designed to reduce the workload on the upper extremities and boost the muscle strength of workers from prolonged repetitive work. The functional jacket designs for the upper limb incorporated a dynamic taping line with an elastic band, three-dimensional support for the abdomen and posterior waist (S2) and an X-shaped line on the scapular region combined with abdominal and posterior waist support (S3). Clothing pressure was adjusted ergonomically for different areas. A standard jacket served as the control (S1). The designs were evaluated based on work posture, electromyography and subjective sensation. S2 and S3 effectively reduced the workload on the upper extremities by decreasing the trapezius muscle, shoulders and waist movement. S3 showed a low muscle-activation level on electromyogram analysis and was excellent in subjective sensation. A functional jacket with optimal compression applied differentially to the upper extremities, with three-dimensional abdominal and posterior waist support and an X-shaped line on the scapula region, can reduce the workload on the upper extremities and boost the core muscle strength to improve work performance.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-02-11
DOI: 10.1108/IJCST-06-2024-0137
Issue No: Vol. ahead-of-print, No. ahead-of-print (2025)
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- Cloth-net: improved hybrid adversarial network with dense vision
transformer for 2D-3D image classification for accurate cloth
recommendation engine-
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Authors: Akanksha Mrinali, Pankaj Gupta
Abstract: The aim of this study is to enhance the performance of cloth recommendation systems by proposing a hybrid adversarial network called Cloth-Net, which integrates Dense Vision Transformers for effective 2D-3D image classification. Cloth-Net combines the strengths of adversarial networks with Dense Vision Transformers to process both 2D and 3D images for improved classification. The model was trained on a large-scale dataset of clothing images, using a hybrid adversarial approach that enhances both feature extraction and image classification accuracy. The methodology also includes data augmentation and transfer learning techniques to optimize the model’s generalization capability. Experimental results demonstrate that Cloth-Net significantly outperforms traditional convolutional neural network-based methods in terms of accuracy, precision, and recommendation quality. The hybrid adversarial framework, together with Dense Vision Transformers, enables the model to better understand complex clothing images, leading to more accurate and personalized recommendations. This study introduces a novel hybrid adversarial model, Cloth-Net, that uniquely combines Dense Vision Transformers with traditional adversarial networks for the first time in the context of 2D-3D image classification. The findings present a substantial improvement in the performance of cloth recommendation engines, making the proposed model valuable for both academic research and practical applications in fashion technology.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-01-29
DOI: 10.1108/IJCST-05-2024-0110
Issue No: Vol. ahead-of-print, No. ahead-of-print (2025)
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- Investigation of electrical conductivity and sensor properties of MWCNT
reinforced nanocomposite textile surfaces-
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Authors: Rusen Inan, Ismail Usta, Yesim Muge Sahin
Abstract: The aim of the study is primarily to ensure the electrical conductivity of the nanocomposite textile surface that is produced. Subsequently, the sensor properties were determined by monitoring the resistance changes under tensile forces. Thermoplastic polyurethane solution was prepared by adding MWCNT and SDS for the production of a nanocomposite textile surface by the electrospinning method. In the present study, it was aimed to improve the conductivity and sensor properties by increasing the surface area via nanotechnological production methods depending on the MWCNT and SDS ratios. It was determined that the vertical and horizontal samples taken from the produced nanocomposite surfaces had electrical properties. In the present study, the relation between the SDS and MWCNT incorporation has been proven not only with the viscosity but also with the conductivity values of the solution. On the other hand, enhanced conductivity is obtained for the SDS-incoorporated nanocomposites for which homogeneous distribution is maintained. The findings of the study indicate that there were resistance changes for the produced nanocomposite surfaces under tension forces, and thus sensor properties were obtained. It has been observed that studies on textile-based sensors have increased in recent years. In these studies, conductive materials are adapted to textile structures by coating and impregnation methods. In the present study, nanocomposite surfaces were obtained by the electrospinning method with the incoorporation of conductive MWCNT and SDS into a thermoplastic polyurethane solution. Owing to the homogeneous distribution of the conductive particles into the composite system, the conductivity of the nanomats was remarkably enhanced. For the obtained nanocomposite mats, resistance change under extension stress is maintained, and thus they can be utilized as strain sensors.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-01-28
DOI: 10.1108/IJCST-02-2024-0051
Issue No: Vol. ahead-of-print, No. ahead-of-print (2025)
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- Research on the antibacterial and anti-pilling properties of
polyester-cotton fabrics by the sol-gel technology-
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Authors: Qi Xiao, Enhao Xie, Linwen Guo, Weifu Wang
Abstract: The purpose of this research is to improve the antibacterial and anti-pilling properties of polyester-cotton fabrics by applying a chitosan-silica coating through sol-gel technology. By optimizing the process parameters, the study aims to enhance the fabrics’ resistance to germs, prevent pilling and maintain their mechanical and functional properties. A transparent sol-gel was obtained by hydrolysis and condensation reactions using silane coupling agent (KH-560), ethyl orthosilicate (TEOS), chitosan and ethanol as precursors and co-solvents, respectively. This sol-gel was employed for the purpose of applying antimicrobial and anti-pilling multifunctional finishes to PC fabrics. An orthogonal experimental design method was employed to optimize the process parameters. The surface morphology and chemical structure of the fabrics were studied using scanning electron microscopy and infrared spectroscopy, both before and after finishing. The fabrics were subjected to testing and analysis to evaluate their antimicrobial and anti-pilling properties, as well as the wearing performance. The best antibacterial and anti-pilling properties are achieved when the volume ratio of TEOS to KH-560 is 1:3, the concentration of chitosan is 10 g/L, the dipping time is 60 min and the water content is 1:2. The fabric exhibits an anti-pilling grade of 4–5 and an antimicrobial rate of 99.99%. The silica/chitosan gel generated a thin and elastic coating on the fiber surface, acting as a protective barrier against external abrasion and enhancing the anti-pilling property by 2–3 grades. The fabric strength increased significantly, while the air permeability remained practically unaltered compared to untreated fabric. The development of advanced materials such as chitosan-modified silica sols holds significant social implications. These materials, with their enhanced properties, can lead to innovations in healthcare, environmental remediation and energy storage, improving living standards and fostering sustainable development. Their widespread adoption could also stimulate economic growth and job creation, fostering a more resilient society. This research introduces an innovative approach using sol-gel technology to enhance the antibacterial and anti-pilling properties of polyester-cotton fabrics. By optimizing the ratio of TEOS to KH-560, chitosan concentration, dipping time and water content, it achieves remarkable results in both performance metrics, offering significant practical value for the textile industry, especially in healthcare and fashion sectors.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-02-05
DOI: 10.1108/IJCST-07-2024-0151
Issue No: Vol. 37, No. 2 (2025)
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- Design and development of graduated compression garment with adhesive
stripes using 3D virtual fitting technology-
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Authors: Ana Černiavskaja, Kristina Ancutienė, Loreta Valatkienė
Abstract: The goal of this research is to utilize 3D virtual fitting technology to design and develop a customized full leg sleeve with graduated compression and strategically placed adhesive stripes, aiming to improve training effectiveness by restricting bending movement in the leg. Knitted fabric and polymer adhesive film were chosen for compression garment development. The design of adhesive stripes was based on Kinesio taping method. Pattern design and 3D visualization was performed using Modaris 3D (CAD Lectra). The compression values were determined by the Laplace equation. The compression full leg sleeve with and without the adhesive stripes were fitted on the virtual mannequin in the squat position in order to determine the influence of adhesive stripes for tensile load in longitudinal direction. The compression values in a virtual garment varied from 23.17 ± 1.94 mmHg in the ankle girth to 13.41 ± 1.50 mmHg in the thigh girth. The difference did not exceed 3 mmHg compared to the planned pressure values. The obtained result showed that purposefully placed adhesive stripes significantly increased the tensile force in the longitudinal direction of the garment in a squat position, so it may improve training effectiveness. 3D virtual fitting represents the fit on a solid body form, which may affect the accuracy of compression garment simulation, as the human body is not rigid. The application of 3D virtual fitting technology in creating customized and functional garments demonstrates its unique contribution to garment prototyping and product development.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-01-31
DOI: 10.1108/IJCST-10-2023-0156
Issue No: Vol. 37, No. 2 (2025)
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- Shielding effectiveness of high-polymer short-staple-based fabric
implanted with the metamaterial structure of “split ring resonator”-
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Authors: Hong Tian, Yayun Li, Xingli Xie, Jindong Ye, Zhe Liu, Xiuchen Wang
Abstract: Electromagnetic shielding (EMS) fabrics composed of cotton, polyester and other high-polymer short-staple fibers are widely utilized in various fields. However, the inevitable pores in these fabrics lead to the leakage of electromagnetic waves, which severely diminishes the fabric’s shielding effectiveness (SE). To address this issue, this paper proposes the implantation of a metamaterial structure known as the “split ring resonator (SRR)” into the fabric. Firstly, the types and principles of SRRs are analyzed. Through electromagnetic simulation and emulation, the effectiveness of SRRs in dissipating electromagnetic waves is confirmed. By selecting different embroidery methods, various shapes of SRRs are implanted into the fabric. Subsequently, through testing and analysis of sample fabrics embroidered with SRRs, it is concluded that implanting appropriate SRRs into pure cotton fabrics and cotton/polyester/stainless steel-blended EMS fabrics can effectively impart or enhance the SE of these fabrics. For pure cotton fabric without inherent SE, the peak SE value can reach over 30 dB within the 6.57 GHz–7 GHz frequency band, and the minimum SE is greater than 10 dB in the 7 GHz–9.99 GHz frequency band. For the cotton/polyester/stainless steel-blended EMS fabric, the improvement in SE across all frequency bands exceeds 10 dB, averaging around 15.6 dB. The circular type SRR demonstrates the most significant improvement in fabric SE. When the substrate is composed of pure cotton or a cotton/polyester/stainless steel blend, the circular SRRs provide an average enhancement of more than 4 dB and 6 dB, respectively, than other shapes. The fewer the holes created by the implantation method, the higher the SE of the fabric after SRR implantation, with the invisible embroidery technique being the most effective. It improves the fabric’s SE by an average of about 2 dB more than flat embroidery and can be up to an average of around 6 dB higher than the backstitch embroidery technique. For every 0.2 cm increase in the size of the SRRs, the average SE increases by about 4 dB, and for every 0.5 cm increase in the spacing between them, the fabric’s SE decreases by an average of more than 2.7 dB. This paper offers a novel approach to counteract the issue of pores reducing the SE of EMS fabrics and provides a new method for developing lightweight, thin, low-cost and high-performance EMS fabric composite materials.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-01-29
DOI: 10.1108/IJCST-06-2024-0133
Issue No: Vol. 37, No. 2 (2025)
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- Demand forecasting in clearance season for fast fashion retail:
a residual learning approach-
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Authors: Nur Gülcan, Dilek Tüzün Aksu, Dionysis Goularas
Abstract: This study focuses on forecasting demand for markdown pricing in situations where historical data are limited and proposes using a hybrid knowledge-based residual (KRL) network to enhance the accuracy of demand predictions in fast fashion retailing. We use a hybrid KRL network structure to increase forecasting accuracy in fast fashion data by combining artificial neural network (ANN) and theoretical demand models (TDMs) such as linear, exponential and multinomial logit. We used a linear demand model (LDM) as a theoretical demand model, which is one of the popular TDMs in the literature, and combined it with neural networks utilizing the residual network structure. We tested it on real fast fashion data to estimate the next week’s demand at the clearance seasons of 5 years. The results underscore KRL’s capability to derive mutual benefits from both neural networks and LDM, especially in the specific context of limited fast fashion data. Furthermore, KRL outperforms LDM and ANN models when used individually in forecasting accuracy. The research paper proposes a scientific, quantitative method for forecasting the sales for markdown settings, combining data driven and TDMs using residual learning thereby resolving the issue of insufficient sales data in the fashion industry.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-01-24
DOI: 10.1108/IJCST-08-2024-0169
Issue No: Vol. 37, No. 2 (2025)
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- Self-supervised learning fabric defect segmentation using anomaly
generation-
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Authors: Kankan Qi, Yanchi Guo, Jian Zhou
Abstract: The problem of fabric defect detection is a particularly challenging task, as the fabric defects occupy only a small portion of the image pixels and it is difficult to collect sufficient samples for training deep learning-based models. The purpose of this work is to present a novel self-supervised learning method to address this problem. In order to solve the problem of lack of defect samples, based on the fabric-specific degree of texture regularity, we propose an anomaly generation method to create synthetic fabric defects by destroying the normal fabric texture. To improve the detection of defects of different sizes, a global–local parallel detection mechanism is proposed. A self-supervised model including an anomaly generation module, a reconstruction subnetwork and a discriminative subnetwork is established to achieve model training without prior anomaly information. The proposed method features self-supervised training, does not require no labelled anomaly data and detects anomalies by distinguishing their distance from normal samples at both global and local levels. When tested on four fabric datasets, our approach outperforms state-of-the-art unsupervised and self-supervised methods and achieves significantly higher localization accuracy. A high-fidelity fabric defects synthesis method is presented to alleviate the problem of collecting numerous fabric defects, providing a reference for other surface anomaly detection problems. The proposed global–local parallel detection mechanism can serve as a reference for other methods dedicated to detecting particular anomalies. The proposed self-supervised network model can effectively locate fabric anomalies without prior labelling information, which could be used as a framework for other model designs.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-01-15
DOI: 10.1108/IJCST-12-2023-0187
Issue No: Vol. 37, No. 2 (2025)
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- Evaluation of graduated compression stockings: a multi-size analysis of
fabric properties and leg pressures-
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Authors: Adriana Gorea, Sarah Megivern
Abstract: The purpose of this study was to investigate the physical properties of a full-size range (S-XXL) of a commonly used brand of medical grade GCS, aimed to provide consistent leg pressures across all sizes, assisting patients recovering from Achilles tendon rupture surgery. This experimental study analyzed the fabric properties of a full-size range of GCS and evaluated their applied pressures on the Ankle and Calf levels of 14 patients recovering from Achilles tendon rupture surgery. ANOVA was run across multiple dependent variables, Density, Thickness, Weight, Air Permeability, Force, Elongation and Stiffness of stocking fabrics. Results revealed significant effects for several factors. Sock Size had a significant main effect on Density, Thickness and Force. Level had a significant main effect on Weight, but no interaction effects were significant. Air Permeability was significantly influenced by its main effect and by its interaction with Sock Size. No significant main effects or interactions were found for Elongation. Both Sock Size and Level had significant main effects on Stiffness. The Pressure results showed that the Level variable had a significant effect on Pressure, explaining 40.4% of the variance in Pressure. Because of the chosen research approach, samples and participants, the research results may lack some generalizability. The results highlight the inconsistent fabric properties across a size range of medical grade GCS, with the larger sizes having smaller differences between pressures on the Calf relative to Ankle than the smaller sizes. This paper fulfils an identified need to study the size range of GCS and the material properties in relation to body pressures. Understanding these differences could help GCS manufacturers improve their sock sizing design process, resulting in more consistent pressure properties across sock sizes, and better therapeutic and recovery patient experience.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-01-09
DOI: 10.1108/IJCST-10-2024-0204
Issue No: Vol. 37, No. 2 (2025)
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- A customization design platform for school uniforms using the Kano model
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Authors: Xue Li, Mei Meng, Xiang Fang Ren, Lei Shen
Abstract: This study aims to explore a methodology based on the Kano model. And use this method to determine user requirement attributes in the field of school uniform customization. To construct a set of processes that can be used as a reference for constructing a clothing customization platform. An optimized quantitative Kano model was applied. Initially, a survey was conducted to assess the current market for customized school uniforms in China. Subsequently, a Kano attribute questionnaire was developed, and experts from both supply and procurement sectors were invited to evaluate it. This was followed by categorizing user demands based on the Kano model’s evaluation criteria and conducting a validity analysis using Cronbach’s alpha coefficient. The priority ranking of user demands was determined through a sensitivity analysis of better-worse coefficients. Ultimately, a platform was established, and a fuzzy comprehensive evaluation was conducted. Regarding user demands, procurement-side demand elements prioritize modular design, fabric libraries and online reviews. In contrast, supply-side demand elements focus on style product libraries, layout adaptation to user habits and the preview effects of 3D models. Elements such as qualification verification, personal information uploading, design draft archiving and main tag categorization have a lesser impact on user satisfaction. The results of the study provide a complete methodological reference for the construction of a garment customization platform. By applying the Kano model, this study categorizes and filters the demands of users for school uniform customization design platforms in China and establishes a 3D virtual display platform aimed at improving user satisfaction.
Citation: International Journal of Clothing Science and Technology
PubDate: 2025-01-09
DOI: 10.1108/IJCST-03-2024-0065
Issue No: Vol. 37, No. 2 (2025)
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- Investigation of effect of recycled polyester ratio and draw frame
passages on flame retardancy of chenille fabric properties-
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Authors: Halil İbrahim Çelik, İbrahim Halil Tekin, Perihan Tekin, Ali Çağlayan, Serdar Saycan
Abstract: In this study, both flame retardancy and sustainability properties were combined in the chenille yarn so that functional and sustainable upholstery fabrics can be produced with optimum energy consumption. The chenille yarn samples were produced from recycled polyester (rPET)-blended binder yarns and fully drawn yarn (FDY) polyester pile yarn. While the pile component of the chenille samples was kept constant, the lock yarns were manufactured as 50% r-PET-50% virgin polyester (PES), 100% r-PET and 100% PES. The binder yarns were also produced in two groups. In the first group, a 2-passage draw frame was used, while a 3-passage draw frame was used in the second group. The chenille yarn samples were applied flame-retardant (FR) finishing. The knitted upholstery fabric samples were produced from chenille yarn samples via flat knitting machines. The knitted fabrics were applied flame retardancy, bursting strength and abrasion resistance tests according to related standards. The test results were analysed, and so the effect of r-PET ratio and draw frame passage number on upholstery fabric flame retardancy, bursting strength and abrasion resistance performance properties were revealed. It was concluded that the number of draw frame passages and the recycled fibre content have no important effect on the flame retardancy. On the other hand, it has been observed that the bursting strength decreases as the recycled fibre content increases and bursting distention results are close to each other. It was seen that the draw frame passage number has no significant effect on both bursting strength and distention. It was revealed that both r-PET fibre content and draw frame passage number have significant effect on abrasion resistance. The samples with 2 draw frame passages provide higher abrasion resistance compared to those with 3 draw frame passage. The lowest abrasion resistance was obtained with 100% r-PET fibre content and the highest abrasion resistance was obtained with 50% r-PET-50% PES. The results will provide enough knowledge for sustainable chenille yarn design. The recycled fibre content and draw frame passage number can be optimised, and so sustainable chenille yarns can be produced with less energy consumption. Future studies will involve producing chenille yarns with different linear densities and varying draw frame combinations, such as 1, 2 and 3 passages.
Citation: International Journal of Clothing Science and Technology
PubDate: 2024-10-28
DOI: 10.1108/IJCST-03-2024-0076
Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
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- A comparative analysis of after-stitch strength reduction in sewing
threads across woven, nonwoven and composite fabric assemblies-
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Authors: Md Vaseem Chavhan
Abstract: This study aims to investigate the factors influencing the reduction in strength of sewing threads after stitching (after-stitch strength reduction) in different fabric assemblies, including nonwoven fabrics. This research expands upon previous studies, which primarily focused on woven fabrics. A full-factorial experimental design was employed, considering three factors: fabric assembly type (woven, nonwoven, composite), yarn type (spun polyester, core-spun polyester) and thread count (30 Tex, 60 Tex). Also, the stitching parameters stitch density (3 spc, 5 spc) and needle count (75 Nm, 100 Nm) were considered. The predictive regression model was also developed with a second-degree order. Tensile testing was conducted on unravelled threads before and after stitching to assess strength reduction. Fabric assembly type significantly impacted after-stitch strength reduction, with the composite assembly exhibiting the highest reduction. Yarn type played a crucial role in the composite assembly; core-spun yarn experienced higher strength reduction compared to spun polyester yarn. Thread count consistently affected strength reduction across all fabric assemblies, with finer threads experiencing higher reductions. Stitch density generally had a positive correlation with strength reduction for woven and nonwoven assemblies, but no significant difference was observed in the composite assembly. Needle count did not significantly impact strength reduction for any fabric assembly. The findings can guide the selection of appropriate sewing threads, yarn types and sewing parameters for different fabric assemblies, including nonwoven fabrics, to optimize seam performance and garment durability. This study contributes to the understanding of how fabric structure, yarn characteristics and sewing parameters interact to influence sewing thread strength reduction in diverse fabric assemblies, including nonwoven fabrics, which were not previously considered in similar studies. This broader investigation provides valuable insights applicable to a wider range of sewing applications.
Citation: International Journal of Clothing Science and Technology
PubDate: 2024-09-30
DOI: 10.1108/IJCST-03-2024-0060
Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
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- The principal component analysis method to study mechanical properties and
denim manufactured garment shrinkage-
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Authors: Faouzi Khedher, Boubaker Jaouachi
Abstract: The purpose of this work is to study the relationship between the fabric’s mechanical properties such as tear strength (TS), breaking strength (BS) and cloth’s dimensional stability (Sh), particularly, after industrial launderings (stone wash, enzyme wash, mixed wash and rinse). Hence, we select the most interrelationships using the principal component analysis (PCA) technique. In this study, the treatments of finishing garments during washing are the important parameters influencing the cloth’s dimensional and the fabric’s mechanical properties. To improve the obtained results, the selected significant inputs are also analyzed within their influence on shrinkage. The polynomial regression model relating the tear strength and the shrinkage of denim fabric proves the effectiveness of the PCA method and the obtained findings. To investigate the matter, the type of washing, and their contributions to shrinkage, four types of fabrics manufactured into pants were used. These fabrics differ not only by their basis weights (medium and heavy weight fabrics) but, also by their compositions (within and without elastane) and their thread count (warp and weft yarn count, twist and density. To evaluate significant results, a factorial design analysis based on an experimental design was established. The choice of these treatments, as well as their design mode, led us to make a complete factorial experimental design. According to the results, the prediction of shrinkage behavior as a function of the process washing input parameters seems significant and useful in our experimental design of interest. As a consequence, it was also concluded that after these input parameters, we can find the relationship between the shrinkage (Shwarp and Shweft) and the mechanical properties such as tear strength (TSwarp and TSweft) and breaking strength (BSwarp and BSweft). Thanks to the PCA, it is very easy to reduce the number of the influent output parameters, and knowing these significant parameters, the prediction of mechanical properties knowing the shrinkage of denim garment, during the process of washing seems successful and can undoubtedly help industrial to minimize the poor workmanship of the finishing quality. This study is very interesting for finishing denim garments. The shrinkage is very important for correcting measures in sewing, considering that a high shrinkage may cause the cancellation of the fit from the client. This type of defect cannot be repaired in the major part of the cases and causes a big loss for the company, moreover the mechanical properties. For this reason, analyzing the value of shrinkage before starting the production cycle is of great importance to apply the right balance to the pattern. The model of predicting the mechanical properties behaviors as a function of the shrinkage denim garment leads manufacturers to eliminate the test of mechanical properties that remain as destructive tests. Moreover, according to the results obtained, it may be concluded that prediction is still accurate through the shrinkage test which is an inevitable test. Even though, these results can bring a huge gain for the garment wash industries. This work presents the first study predicting a relationship between the mechanical properties and denim garment shrinkage, applying the PCA technique to minimize the all-output parameters that are not significant or correlated with each other. Besides, it deals with the relationship developed between the fabric’s mechanical properties such as tear strength (TS), breaking strength (BS) and cloth’s dimensional stability (Sh), particularly, after industrial launderings (stone wash, enzyme wash, mixed wash and rinse). Moreover, it is notable to mention that the originality of this study is to let to the garment wash industries to save in production time of orders and also in quality.
Citation: International Journal of Clothing Science and Technology
PubDate: 2024-09-02
DOI: 10.1108/IJCST-11-2023-0173
Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
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- Design of passive radiative heating nanocomposite films by managing
natural radiation energy-
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Authors: Sibel Kaplan, Dilara Melek Demirbek, Nazife Korkmaz Memis
Abstract: Personal thermal management by controlling the radiation energies of both the body and the sun can be used in all environments and contributes to sustainability components with the advantages of energy saving, low chemical usage and comfort enhancements under dynamic conditions. In this study, passive radiative heating nanocomposite films were produced using sodium alginate as the matrix and zinc oxide (ZnO) and aluminum oxide (Al2O3) nanoparticles as nanofillers having far infrared radiation reflecting, hence passive heating functions. Nanocomposite film solutions were prepared by stirring sodium alginate powder, deionized water, ZnO and Al2O3 nanoparticles (20% wt of matrix polymer) with surfactant using magnetic and ultrasonic stirrers in turn. Films produced within Petri dishes after drying at room temperature were analyzed by FT-IR, UV-VIS-NIR spectroscopy and SEM for chemical, radiation management and morphological characteristics, respectively. Emissivity values giving idea about the heating performances of the films were determined with an IR camera and a hotplate system. Moreover, direct heating performances were measured by the hotplate system including a far-infrared lamp. Results showed that the emissivity of the films increased by approximately 18% and 16% with ZnO and Al2O3 nanoparticles, respectively. Moreover, NaAlg–Al2O3 nanocomposite film exhibited passive radiative heating performance of 3.58 °C, higher than the heating performance of NaAlg–ZnO nanocomposite film which is 2.97 °C when compared to the reference NaAlg film. These results indicate that both NaAlg–ZnO and especially NaAlg–Al2O3 nanocomposite films have excellent far-infrared emission and absorption properties ensuring a significant heating effect. In addition to other clothing types, the heating performance obtained with the produced nanocomposite structures may be applied to different types of cosmetic/medical applications (beauty mask, wound dresses, etc.) enabling skincare/healing with the advantage of the sodium alginate matrix.
Citation: International Journal of Clothing Science and Technology
PubDate: 2024-08-05
DOI: 10.1108/IJCST-01-2024-0019
Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
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- Innovative 3D-printed surfaces for efficient water harvesting from air
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Authors: Furkan Turan Koyun, Sema Sabur, Güldemet Başal, Hüseyin Günerhan
Abstract: The purpose of this study is to develop nature-inspired 3D surfaces for atmospheric water harvesting. Initially, cylindrical-shaped protrusions were produced utilizing a 3D printer to obtain a surface with a high surface area. Subsequently, an electrospraying technique was employed to coat the tips of these hydrophobic protrusions with hydrophilic nano-scale particles and fibers, utilizing polyamide 6 (PA6) or PA6/chitosan (CH) blends. In the next stage of the study, the impact of protrusion shape was investigated by fabricating surfaces with cylindrical, conical and tree-shaped protrusions. Following the production of 3D surfaces, PA6 was electrosprayed onto the protrusions to achieve varied wettability patterns on the 3D surface. Finally, the water collection rates and capacities of the surfaces were evaluated. Water collection tests demonstrated that PA6-coated surfaces exhibited greater water collection capacity compared to untreated surfaces. Furthermore, the addition of CH enhanced the water collecting efficiency of the 3D surface. It was found that the shape of the protrusions significantly influenced water collection capacity. Particularly, cone-shaped protrusions exhibited the highest water collecting capability among the different shapes tested. In this study, 3D printing and electrospraying techniques were combined to create 3D surfaces characterized by high surface area, along with hydrophilic and hydrophobic regions to produce superior surfaces for atmospheric water harvesting.
Citation: International Journal of Clothing Science and Technology
PubDate: 2024-07-15
DOI: 10.1108/IJCST-02-2024-0050
Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
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- Sustainable pre-treatment of cellulose knitwear in digital pigment
printing processes
Open Access Article-
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Authors: Martina Glogar, Sanja Ercegovic Razic
Abstract: In the field of research on the application of digital printing to textile materials, there are still many research issues that arise from the very demanding interaction of digital printing technology and the complex, heterogeneous surface system of textile materials. This is precisely why the area of pre-treatment of textile materials is in need of research, and the purpose of this research was to establish the level of influence of physical and chemical activation of the textile surface with plasma and the possibility of improving the quality of the print and colour reproduction. The paper deals with the possibility of applying argon and oxygen cold low-pressure plasma in the processing of cellulose knitted fabrics, with the aim of improving the quality of the print and colour reproduction in digital pigment inkjet printing. The selected raw material samples were 100% raw cotton and lyocell. After plasma treatment, the samples were printed by digital ink jet printing with water-based pigment printing ink. An analysis of the micromorphological structure of untreated and plasma-treated samples before and after printing was carried out, and a comparative analysis of the colour of the printed elements was carried out depending on the pre-treatment. The conducted research showed a positive influence of plasma pre-treatment on the coverage of the fibre surface with pigments, the uniformity of pigment distribution along the fibre surface and the uniformity of the distribution of the polymeric binder layer. This has a positive effect on colour reproduction. Also, certain improvements in colourfastness to washing were obtained. Considering the complexity of the topic, although exhaustive, this research is not sufficient in itself, but opens up new questions and gives ideas for further research that must be carried out in this area. Also, this kind of research contributes to the possibility of adopting the idea of industrial plasma transformation, as an ecologically sustainable functionalisation of textiles, which has not yet been established. This research is certainly a contribution to the establishment of acceptable textile pre-treatment methods in the field of digital printing, as one of the key quality factors in digital textile printing (DTP). Considering the still large number of obstacles and unanswered questions encountered in the field of digital printing on textiles, this kind of research is a strong contribution to the understanding of the fundamental mechanisms of the complex interaction between printing ink and textile.
Citation: International Journal of Clothing Science and Technology
PubDate: 2024-07-09
DOI: 10.1108/IJCST-03-2024-0061
Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
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- Textile wastewater: COD removal via Box–Behnken design, Fenton method,
and machine learning integration for sustainability-
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Authors: Selman Turkes, Hakan Güney, Serin Mezarciöz, Bülent Sari, Selami Seçkin Tetik
Abstract: The widespread use of washing machines in textile dyeing and finishing boosts product quality while leading to significant wastewater production. This wastewater poses environmental risks due to the textile industry's high pollution levels and water consumption. Sustainability hinges on minimizing water usage and treating wastewater for reuse. This study employs Matlab R2020a and Python 2023 to model experimental designs for treating textile production wastewater using the Fenton oxidation method, aiming to address sustainability concerns in the industry. The Fenton oxidation process's efficacy and optimal operating conditions were determined through experimental sets employing the Box–Behnken design. Assessing machine learning algorithms on the data, Matlab R2020a utilized an artificial neural network (ANN), while Python 2023 employed support vector regression (SVR), decision trees (DT), and random forest (RF) models. Evaluation of model performance relied on regression coefficient (R2) and mean square error (MSE) outcomes. This methodology aimed to refine the Fenton oxidation process and identify the most efficient parameters, leveraging a combination of experimental design and advanced computational techniques across different programming platforms. The study identified optimal conditions: pH 3, Fe+2 concentration of 0.75 g/L, and H2O2 concentration of 5 mM, yielding 87% COD removal. The Box–Behnken design achieved a high R2 of 0.9372, indicating precise predictions. Artificial neural networks (ANN) and support vector regression (SVR) exhibited successful applications, notably achieving an R2 of 0.99936 and low MSE of 0.00416 in the ANN (LOGSIG) model. However, decision trees (DT) and random forests (RF) proved less effective with limited datasets. The findings underscore technology integration in treatment modeling and the environmental imperative of wastewater purification and reuse. This study, in which water use and wastewater treatment are evaluated with technological integration such as machine learning and data management, reveals how to contribute to targets 6, 9, 12, and 14 within the scope of UNEP 2030 sustainable development goals.
Citation: International Journal of Clothing Science and Technology
PubDate: 2024-06-14
DOI: 10.1108/IJCST-02-2024-0045
Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
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- Analysing the effect of mechanically recycled cotton fibres from
pre-consumer wastes on mechanical and fastness properties of knitted
fabrics-
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Authors: Burak Sari, Memik Bunyamin Uzumcu, Kubra Ozsahin
Abstract: The study aimed to investigate the impact of mechanically recycled cotton fibres from pre-consumer waste, blended with virgin cotton at varying ratios, on the mechanical and fastness properties of knitted fabrics. Single jersey fabrics were produced using open-end rotor yarns with two different yarn counts, which were made from cotton blends obtained at three different mechanical recycled cotton blend ratios. The fabrics were then comparatively analysed for pilling resistance, bursting strength, dimensional stability, and fastness to perspiration, water, and rubbing. The investigations included fabrics made from 100% virgin cotton to determine the impact of mechanically recycled cotton fibres on the final fabric properties. It was observed that using MR-CO at different ratios generally produced results similar to the usage properties obtained when using virgin cotton. The study looked in detail at the effect of using mechanically recycled cotton (MR-CO) on the yarn properties and the mechanical and colour fastness properties of the fabrics produced using them. It was found that MR-CO has the potential to be an alternative fibre source to virgin cotton, not only mechanically but also in terms of colour fastness. Previous studies have commonly used MR-CO in fixed ratios or by incorporating various fibres into the blend. However, in this study, we determined the suitability of fabrics for their intended use by gradually increasing the MR-CO blend ratios and more clearly assessing the impact of MR-CO on fabric properties.
Citation: International Journal of Clothing Science and Technology
PubDate: 2024-06-10
DOI: 10.1108/IJCST-03-2024-0059
Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
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- The rise of sustainable approaches in development of waterproof breathable
fabrics for garment: a systematic literature review-
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Authors: Abhishek Kumar, Manpreet Manshahia
Abstract: The aim of this study is to present an overview of sustainable practices in the development of waterproof breathable fabrics for garments. It aims to provide insights into the current state of academic research in this domain and identify and analyze major sustainable trends in the field. This study conducts a thorough examination of research publications sourced from the Scopus database spanning the years 2013–2023 by employing a systematic approach. The research utilizes both descriptive analysis and content analysis to identify trends, notable journals and leading countries in sustainable waterproof breathable fabric development. The study reveals a notable increase in studies focusing on sustainable approaches in the development of waterproof breathable fabrics for garments. Descriptive analysis highlights the most prominent journal and leading country in terms of research volume. Content analysis identifies four key trends: minimizing chemical usage, developing easily degradable materials, creating fabrics promoting health and well-being and initiatives to reduce energy consumption. The main limitation of this research lies in its exclusive reliance on the Scopus database. The insights derived from this study offer practical guidance for prospective researchers interested in investigating sustainable approaches to developing waterproof breathable fabric for garments. The identified trends provide a foundation for aligning research endeavors with contemporary global perspectives, facilitating the integration of sustainable methodologies into the garment industry. This systematic literature review contributes original insights by synthesizing current research trends and outlining evolving sustainable practices in the development of waterproof breathable fabrics. The identification of key focus areas adds a novel perspective to existing knowledge.
Citation: International Journal of Clothing Science and Technology
PubDate: 2024-03-22
DOI: 10.1108/IJCST-01-2024-0015
Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
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- A method for designing face shields using dynamic 3D head data
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Authors: Yeonghoon Kang, Sungmin Kim
Abstract: To analyze the changes in craniofacial morphology during speaking and wearing masks using three-dimensional head data and to develop a design method for ergonomic face shields. Around six types of face postures for three-dimensional measurement were selected; a total of 180 head data of 40 men in their 20s and 30s were used. About 17 landmarks and 23 body dimensions were measured for analysis. Among the 23 anthropometric dimensions, eight in posture “a,” two in posture “i,” seven in posture “u,” ten in KF94 and ten in N95 were found to change significantly. Previous studies and public health recommendations selected three key dimensions for face shield design. A face shield design method using selected dimensions as parameters was developed. To improve public health and enhance social interaction during pandemics or in environments requiring facial protection. This can lead to increased compliance with public health guidelines and reduce discomfort and communication barriers caused by ill-fitting face shields. By developing an ergonomic face shield design that accommodates variations in craniofacial morphology during speaking and mask, the study addresses the need for more comfortable and effective protective equipment. The face shield designed using the methodology developed in this study was verified on a digital head model to demonstrate a good fit.
Citation: International Journal of Clothing Science and Technology
PubDate: 2024-12-26
DOI: 10.1108/IJCST-06-2024-0130
Issue No: Vol. 37, No. 2 (2024)
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- Peppermint extract-compound nanofiber production and characterization
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Authors: Nilşen Sünter Eroğlu, Suat Canoğlu
Abstract: As a result of referee evaluation, the subject scope of the article has been expanded. Previously, only polycaprolactone (PCL) loaded with peppermint extract had been studied. As a result of peer review, nanostructure production was made with peppermint-loaded polylactic acid (PLA). Literature information about PLA polymer has been added to the Introduction section. Additionally, to analyze the presence of peppermint extract in Fourier transform infrared (FTIR) measurements, a comparison was made with 100% PCL, 100% PLA and 100% peppermint extract. In order to observe the effect of polymer type, evaluations were made between the produced peppermint-loaded nanostructures containing two different polymers. Mechanical, structural and morphological properties of the produced nanostructures were measured. The main purpose of the study is to analyze and evaluate peppermint-loaded nanostructures on different polymers. Nanofiber structures were produced by the electrospinning process due to their attractive properties such as low cost, flexibility, integrability and high efficiency. The production parameters of the nanofiber structure produced by the electrospinning process, mechanical measurements, fiber morphologies with scanning electron microscope (SEM) and structural characterization with FTIR measurement were analyzed, and its potential in possible usage areas was interpreted. In this study, the production of nanostructures containing peppermint extract with PCL and PLA polymers, which are various biodegradable and biocompatible polymeric materials, was successfully achieved. In the studies carried out, nanofiber structures with positive properties such as low cost, easy accessibility, flexibility, integrability and sustainability were produced. When the two nanofiber structures produced were compared, it was observed that the peppermint extract nanofiber structure containing PCL provided better morphological and mechanical properties, such as higher strength, thinner fibers' diameter and a smooth and homogeneous surface, compared to the peppermint core nanofiber structure containing PLA. It has been observed that PCL polymer is more advantageous in obtaining nanofibers under the same environmental conditions and the same parameters. The addition of peppermint extract caused an approximately 25% loss in strength in nanostructures containing PCL polymer compared to nanostructures containing 100% PCL. The strength loss in PLA nanostructures containing peppermint extract is approximately 90% compared to nanostructures containing 100% PLA. This situation is associated with the regular arrangement of nanostructures containing PCL. In conclusion, incorporating peppermint extract into the nanofiber structures fabrication process offers several benefits, including enhanced antimicrobial properties and potential bioactive effects. In the study, a uniform and suitable-for-use nanofiber structure with a smooth and partially beaded surface was obtained by an electrospinning method using peppermint extract and PCL and PLA polymers. Morphological evaluation was made with SEM images of the obtained nanofiber structure, and the presence of peppermint extract in the nanofiber structure was determined by the FTIR analysis. In the mechanical analysis, a decrease was observed in the elongation at break and tensile strength values of nanostructures loaded with mint extract, but this decrease did not prevent the production and use of the nanofiber structure.
Citation: International Journal of Clothing Science and Technology
PubDate: 2024-12-17
DOI: 10.1108/IJCST-02-2024-0043
Issue No: Vol. 37, No. 2 (2024)
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- Investigation of the effect of weave and elastane yarn use on auxetic
woven fabric formation and various physical performance parameters-
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Authors: Mine Akgun, Recep Eren, Fatih Suvari, Tuğba Yurdakul
Abstract: Materials with negative Poisson’s ratio are known show improved performance properties. By designing woven fabric structures with auxetic properties, it would be possible to add many functional features to the structure in a single step compared to conventional fabric structures. This study investigated the weave designs for forming auxetic woven fabric structures and also the effects of using elastane yarns on Poisson’s ratio and possible auxetic performances. Weave pattern designs consisting of re-entrant honeycomb and re-entrant zigzag forms, created by long floats and one-to-one intersections of yarns, were included in fabric structure. In addition, fabrics were woven by inserting weft yarns with and without elastane component to evaluate the effect of using elastane component on the auxetic performance. For this purpose, fabrics were woven with 100% polyester warp and weft yarns. Measurement of air permeability and % wetting area of fabrics under different elongations were carried out. Results showed that NPR could be obtained from the designed patterns creating re-entrant honeycomb and re-entrant zigzag geometrical forms on the fabric surface. Also, it was found that the use of elastane yarn had an improving effect on auxetic performance of the woven fabrics. By designing auxetic structured woven fabrics could be preferred in areas of use where clothing comfort was desired, due to the transverse expansion behavior as a result of the auxetic effect due to tension and the resulting pore opening effect.
Citation: International Journal of Clothing Science and Technology
PubDate: 2024-11-26
DOI: 10.1108/IJCST-04-2024-0092
Issue No: Vol. 37, No. 2 (2024)
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- Fashion cloth image categorization and retrieval with enhanced intensity
using SURF and CNN approach-
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Authors: Navneet Kaur, Shreelekha Pandey, Nidhi Kalra
Abstract: The attraction of online shopping has raised the demand for customized image searches, mainly in the fashion industry. Daily updates in this industry increase the size of the clothing database at a rapid rate. Hence, it is crucial to design an efficient and fast image retrieval system owing to the short-listing of images depending upon various parameters such as color, pattern, material used, style, etc. This manuscript introduces an improved algorithm for the retrieval of images. The inherited quality of images is first enhanced through intensity modification and morphological operations achieved with the help of a light adjustment algorithm, followed by the speeded up robust feature (SURF) extraction and convolutional neural networks (CNN). The results are validated under three performance parameters (precision, recall and accuracy) on a DeepFashion dataset. The proposed approach helps to extract the most relevant images from a larger dataset based on scores conferred by multiple cloth features to meet the demands of real-world applications. The efficiency of the proposed work is deduced from its effectiveness in comparison to existing works, as measured by performance parameters including precision, recall and F1 score. Further, it is also evaluated against other recent techniques on the basis of performance metrics. The presented work is particularly advantageous in the fashion industry for creating precise categorization and retrieving visually appealing photographs from a diverse library based on different designs, patterns and fashion trends. The proposed approach is quite better than the other existing ML/DL-based approaches for image retrieval and classification. This further reflects a significant improvement in customized image retrieval in the field of the fashion industry.
Citation: International Journal of Clothing Science and Technology
PubDate: 2024-11-22
DOI: 10.1108/IJCST-03-2024-0074
Issue No: Vol. 37, No. 2 (2024)
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