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Journal articles on the topic 'Yarn quality parameters'
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1
Raian, Shahriar, Jamal Hossen, Subrata Kumar Saha, Emdadul Haque, Siyam Quddus Khan, and Kazi Rezwan Hossain. "Prioritising Yarn Quality Via Varying Top Roller Hardness: A Fuzzy Application." Textile & Leather Review 7 (May 23, 2024): 854–71. http://dx.doi.org/10.31881/tlr.2024.068.
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In recent years, the spinning or yarn manufacturing sector has seen remarkable technological advancements, emphasizing high-quality yarn production, especially for cotton combed ring spun yarns. In the case of better quality ring spun combed yarn, each part of the ring frame is significant. To fulfil this issue, this study focuses on understanding the impact of the drafting roller hardness on cotton-combed ring-spun yarn quality. It delves into how ten top and bottom roller hardness combinations influence yarn quality parameters. The cotton combed yarns underwent rigorous testing after spinning on ring frames with varying drafting roller hardness. Key quality parameters studied included yarn Imperfection Index (IPI), Unevenness (Ue%), Hairiness (Hi), Elongation at break (Eb%), and Count Strength Product (CSP), and Tenacity (Te). The primary insight was that extreme roller hardness adversely affects all parameters except Elongation at the break value obtained for the shore hardness value of 80/83. Yarns produced using medium-hardness rollers showcased fewer imperfections due to more consistent fibre flow and minimized drafting slippages, resulting in an even twist. These findings are pivotal for the yarn manufacturing industry, hinting at potential refinements in production methods. The usage of the Fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory) methodology also determined that Te CSP) and IPI values significantly influence the combed yarn quality when adjusting roller hardness, whereas Hi is the least influential. Therefore, this study offers twofold insights: determining the optimal roller hardness and identifying the most affected quality parameters.
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Abdulazizov, Shokirjon, Jamshid Yuldashev Qambaraliyevich, Khusankhon Bobojanov Tokhirovich, and Akbarkhon Sidikov Khojiakhmadkhanovich. "VISUALIZING SPUN YARN DEFORMATION: INSIGHTS FROM OPTICAL INSTRUMENTATION." American Journal of Engineering and Technology 6, no. 4 (2024): 12–21. http://dx.doi.org/10.37547/tajet/volume06issue04-03.
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This article presents a comprehensive analysis of key quality indicators for spun yarns, focusing on yarns with a linear density of T=20 (Ne=30) tex produced on both simple and compact ring spinning machines. Through the utilization of optical instrumentation, various parameters including relative breaking strength (Rkm), strength, elongation at break (E %), and hairiness (H %) were meticulously examined to evaluate yarn quality. The study delves into the assessment of yarn unevenness (CV %) as a crucial quality metric, aiming to provide insights into the deformation characteristics of spun yarns. By employing advanced optical techniques, such as high-resolution imaging and precise measurements, the deformation behaviour of yarns under different spinning conditions is elucidated. The findings shed light on the influence of spinning machine type on yarn quality parameters, revealing nuanced differences in strength, elongation, and hairiness between simple and compact spinning processes. Additionally, the analysis highlights the correlation between yarn deformation and overall yarn quality, emphasizing the significance of understanding deformation mechanisms in optimizing textile manufacturing processes. Through a rigorous examination of these quality indicators, this research contributes valuable insights into the intricate dynamics of spun yarn deformation and its implications for textile production. The utilization of optical instrumentation offers a novel approach to visualize and quantify yarn deformation, providing a deeper understanding of the factors influencing yarn quality and performance in industrial settings.
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DUC TRUNG, TRAN, HUONG CHU DIEU, and TUAN DAO ANH. "INFLUENCE OF SOME WINDING PARAMETERS ON HAIRINESS OF YARN AFTER WINDING PROCESS." Fibres and Textiles 29, no. 4 (2023): 29–37. http://dx.doi.org/10.15240/tul/008/2022-4-004.
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Hairiness is an important quality parameter of yarn after winding process. It affects not only the quality of yarn, but also the productivity of the warping, weaving, knitting machines as well as the quality of produced fabrics. Hairiness is influenced by the factors of raw materials, technology and equipment at all stages of yarn production. This article presents the results of experimental research on the simultaneous influence of four typical winding parameters, including: Winding speed (Z1), the load on the friction discs of the yarn tensioner (Z2), the distance between the bobbin and the yarn guide (Z3) and the pressure of package on the grooved drum (Z4) to the increasing percentage of the hairiness of the yarns after winding compared to that before winding. Yarn hairiness was measured by Uster tester 5. By using the second-order orthogonal experimental planning, together with the support of Excel 2019 and Design Expert 11 software, an experimental matrix and mathematical models describing the relationship between the four winding parameters and increasing percentage of the hairiness of three types of yarn (carded Ne 31/1 CVCD, combed Ne 30/1 CVCM, combed Ne 30/1 COCM) are established. The research result is the scientific basis for selecting the optimal winding parameters in order to achieve the required increase in hairiness of the yarn after winding or predict hairiness increase of the yarns before winding.
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Sh.R., Fayzullaev, Rajapov O.O., Kojametov B.T., and Kolondorov M.J. "EFFECT OF THREAD ON YARN QUALITY OF COTTON/POLYESTER 80/20% BLEND YARN." International Journal of Advance Scientific Research 03, no. 02 (2023): 24–32. http://dx.doi.org/10.37547/ijasr-03-02-04.
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The mechanical properties, thickness and uniformity of the yarn, deformations of its components and the ability of the yarn to withstand repeated forces, as well as different degrees of breakage of yarns in spinning machines, depend on the twist of the yarn. The productivity of spinning machines also depends on the twist of the thread, because at a constant speed of rotation of their components, their productivity is inversely proportional to the twist of the thread. Therefore, it is important to choose the optimal twist of the thread . The scientific article presents the results of the study of the effect of the number of twists given to the cotton/polyester 80/20% mixed yarn on the quality parameters of the yarn. P wax/polyester 80/20% mixed yarn 14.7 tex ( Ne 40 /1 ) in 850, 918 and 988 twists on ring spinning machines prepared. The quality indicators of the finished yarns were determined using USTER test equipment The unevenness and mechanical properties of mixed yarns and their coefficients of variation were analyzed. As a result, it was determined that the coefficients of variation of the cotton/polyester 80 / 20% mixed yarn between twist 850 and 918 in terms of unevenness indicators decrease, the tensile strength, breaking strength and breaking work indicators of the yarns increase.
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Rashid, Mohammad Mamunur, KZM Abdul Motaleb, and Ayub Nabi Khan. "Effect of flat speed of carding machine on the carded sliver and yarn quality." Journal of Engineered Fibers and Fabrics 14 (January 2019): 155892501984518. http://dx.doi.org/10.1177/1558925019845183.
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Processing parameters play an important role in influencing the quality of the final product in any kinds of production. The aim of this project is to observe the quality of the carded sliver and yarn by applying different flat speeds on the carding machine while the other machine parameters were fixed. Five flat speeds (200, 240, 280, 320, and 360 mm/min) have been used to produce slivers and yarns. Sliver fineness of Ne0.11 and yarn of two different counts (Ne24 and Ne30) were produced for assessing the quality. It is found that the neps, short fibers, and unevenness of sliver and yarn are reduced proportionally with the increase of flat speed, whereas the tensile properties of yarn are increased. The unevenness and tensile properties are found to be best for flat speed 360 mm/min with significant increasing of waste percentage. The Ne24 and Ne30 cotton yarns have comparable unevenness and tensile properties. The quality of yarn improved continuously as the yarn becomes finer.
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Ahmed, Farooq, Ghulam Yasin Shaikh, and Ashfaq Ahmed Pathan. "Effect of Lowering Twist Levels on Quality Parameters of Rotor Spun Cotton Yarn." July 2016 35, no. 3 (2016): 425–30. http://dx.doi.org/10.22581/muet1982.1603.12.
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Investigations were made to explore the influence of lowering twist level on quality characteristics of rotor spun yarn. Three levels of yarn linear density (i.e. 40, 35 and 30 tex) and five levels of twist (i.e. 700, 600, 550, 500, and 450) were employed during yarn spinning trials. Each twist multiple was investigated at all linear densities for tensile strength, elongation, total CVm (Coefficient of Mass Variation) imperfection index and hairiness. 100% cotton yarn samples were prepared on Reiter R-40 at rotor speed of 90,000 rpm. Determination of elongation, yarn strength, hairiness, mass variation, and total imperfections index was carried out on Uster Tensorapid-4 and Uster Tester-4 as per set standards of ISO standard test methods. Based on investigations it is established that yarn strength and elongation declined minutely (Insignificant) with lowering twist levels but still can be confidently used for knitting yarns. However, significant improvement in total imperfection index and marginal enhancement in CVm were experienced.
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Karakaş, Esra, Melik Koyuncu, and Mülayim Öngün Ükelge. "Finite Mixture Model-Based Analysis of Yarn Quality Parameters." Applied Sciences 15, no. 12 (2025): 6407. https://doi.org/10.3390/app15126407.
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This study investigates the applicability of finite mixture models (FMMs) for accurately modeling yarn quality parameters in 28/1 Ne ring-spun polyester/viscose yarns, focusing on both yarn imperfections and mechanical properties. The research addresses the need for advanced statistical modeling techniques to better capture the inherent heterogeneity in textile production data. To this end, the Poisson mixture model is employed to represent count-based defects, such as thin places, thick places, and neps, while the gamma mixture model is used to model continuous variables, such as tenacity and elongation. Model parameters are estimated using the expectation–maximization (EM) algorithm, and model selection is guided by the Akaike and Bayesian information criteria (AIC and BIC). The results reveal that thin places are optimally modeled using a two-component Poisson mixture distribution, whereas thick places and neps require three components to reflect their variability. Similarly, a two-component gamma mixture distribution best describes the distributions of tenacity and elongation. These findings highlight the robustness of FMMs in capturing complex distributional patterns in yarn data, demonstrating their potential in enhancing quality assessment and control processes in the textile industry.
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Oncul, Kursat. "Quality optimization and process capability analysis of ring spun Supima cotton yarn." Materials Testing 63, no. 10 (2021): 943–49. http://dx.doi.org/10.1515/mt-2021-0027.
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Abstract The response surface method and process capability analysis were conducted in this study to improve evenness, hairiness, imperfections, and tensile strength of ring spun Supima cotton yarn by optimizing values of spinning parameters including traveler mass, yarn density, spindle speed, and yarn twist. The yarns were spun into three densities: 20 Ne, 30 Ne, and 38 Ne. An USTER Tester 5-S800 was used to evaluate the irregularity parameters of yarn. A Lloyd tester was also used to determine the yarn breaking load. The response surface method was applied to optimize the statistical values obtained from the tests of the yarns produced based on the combination values of system parameters. Each response was subjected to a response surface design study, and the optimal values were achieved by using a response optimizer to perform multiple response optimization. Interpreting the response surface design results yielded information such as the absolute values of effects, response degree of significance, data compatibility, and model suitability. Individual desirability, composite desirability, different estimates for each response, and the relationship between response and system variables were all revealed by interpreting the response optimization results. The capability indices of process capability analysis were used to compare process performance before and after response optimization. By interpreting the capability indices’ values of process capability analysis, the capability of the process to meet requirements and improvement potential were acquired. The data was analyzed by implementing Minitab software (Version 19).
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Rutkowski, Jacek. "Analysis of the Strength Parameters of Worsted and Component Spun Yarns after the Rewinding Process." Fibres and Textiles in Eastern Europe 26, no. 2(128) (2018): 32–37. http://dx.doi.org/10.5604/01.3001.0011.5736.
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The notion of yarn is understood as a continuous textile product of theoretically endless length and circle-like cross-section, made of staple or continuous fibres. A yarn leaves the spinning mill in a raw state and is used to produce some fabrics, but mostly it is subjected to the process of finishing. The yarn undergoes preparatory processes, such as winding, doubling, twisting, paraffin treatment, singeing and dyeing, depending of the final fabric type. Yarns are rewound on winding frames, and computers control operation of the rewinding frames and systematically monitor the yarn parameters. An electronic cleaner removes yarn defects, whose size has been saved in the computer memory. The purification of yarn improves its quality, resulting in a decrease in the number of breaks in further technological processes. A lower number of yarn breaks contribute to an increase in machine efficiency (weaving and knitting machines). The experimental section of the study is divided into two parts. The first includes tests of yarn strength parameters before and after the rewinding process. It was established in the process of cleaning that the yarn during rewinding affects the strength of wool and blended yarns. In the second part, the strength parameters of yarn doubling points after the rewinding process for various variants of the splicer setting were tested. The blowing time in the doubling chamber was changed and the importance of using the thermosplicer for the yarn joint strength was established.
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Ghanmi, Hanen, Adel Ghith, and Tarek Benameur. "Open-End Yarn Properties Prediction Using HVI Fibre Properties and Process Parameters." Autex Research Journal 17, no. 1 (2017): 6–11. http://dx.doi.org/10.1515/aut-2015-0026.
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AbstractThis article provides three models to predict rotor spun yarn characteristics which are breaking strength, breaking elongation and unevenness. These models used noncorrelated raw material characteristics and some processing parameters. For this purpose, five different cotton blends were processed into rotor spun yarns having different metric numbers (Nm10, Nm15, Nm18, Nm22, Nm30 and Nm37). Each count was spun at different twist levels. Response surface method was used to estimate yarn quality characteristics and to study variable effects on these characteristics. In this study, predicting models are given by the analysis of response surface after many iterations in which nonsignificant terms are excluded for more accuracy and precision. It was shown that yarn count, twist and sliver properties had considerable effects on the open-end rotor spun yarn properties. This study can help industrial application since it allows a quality management-prediction based on input variables such as fibre characteristics and process parameters.
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Et. al., Yuldashev Alisher Tursunbayevich,. "Investigation of Influence ofa New Twist Intensifier on the Properties of the Twisted Yarn." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 5 (2021): 1943–49. http://dx.doi.org/10.17762/turcomat.v12i5.2275.
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The article is devoted to the study of the properties of the yarn obtained by the methods of ring and rotor spinning, for twisted yarn, produced on a VTS-09 double twist machine made by Volkmann (Germany). Experiments were carried out on two typesof spinning yarns with yarn counts Ne 20/2 and 12/2 in the existing design (control) and the new design, flexible element with equal tension and twist intensifier and compared the effects of the resulting twisted yarn for quality parameters. Mathematical statistical methods (single-factor analysis of variance) were used to assess the quality of twisted yarn. Experiments have shown that the use of a new design nozzle reduces the vibration of the yarn, which leads to a uniform distribution of twists along the length of the twisted yarn, increases its tensile strength and improves the quality of the twisted yarn.
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Anand, K. T., A. John Rajan, and K. V. Narayanan. "Factors Affecting Leadtime in Spinning Mills." Applied Mechanics and Materials 813-814 (November 2015): 1154–64. http://dx.doi.org/10.4028/www.scientific.net/amm.813-814.1154.
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An investigation of the factors which affect lead time in spinning mills producing carded and combed counts is reported. Data were collected from 27 mills producing 40 Ne Carded Yarn and 9 mills producing 40 Ne Combed Yarn. A number of 13 parameters which affect lead time were identified and they are FQI (Fibre Quality Index), Roving Production, CSP (Count Strength Product), Yarn Realisation, Spindle Production, Top Arm Roller Pressure (Front), Top Arm Roller Pressure (Middle), Top Arm Roller Pressure (Back), End Breaks, UKG, HOK (the number of Operative Hours required to produce 100 kg of yarn), YQI (Yarn Quality Index), Machine Utilisation. Multiple linear regression analysis have been carried out to find out the dominant parameters which affect lead time. While 71.4% of the variables account for lead time in respect of carded counts, about 78.4% of the variables have dominating influence in combed yarns.
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Lv, Li Bin, and Mei Du. "Research of Relation between Card Sliver Quality and Yarn Quality." Advanced Materials Research 821-822 (September 2013): 426–30. http://dx.doi.org/10.4028/www.scientific.net/amr.821-822.426.
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To research relation of card sliver quality and yarn quality, influence degree of card sliver parameters on yarn quality was analyzed through gray incidence analyses method and least square method, the concrete formula was got, it is feasible for production to adjust carding processing in time, enhance yarn quality stably.
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Mankodi, Hireni, and Pravin Patel. "STUDY THE EFFECT OF COMMINGLING PARAMETERS ON GLASS / POLYPROPYLENE HYBRID YARNS PROPERTIES." AUTEX Research Journal 9, no. 3 (2009): 70–73. http://dx.doi.org/10.1515/aut-2009-090303.
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Abstract The objective of this paper is to discuss effect of commingling parameter on characteristics of Glass/Polypropylene commingled hybrid yarns to get homogenous mix of matrix and reinforcement elements in the final yarn. A commingling machine developed to produce hybrid yarn using two techniques viz. mingling technique and hollow spindle wrapping technique using single machine is highlighted .The machine can run at speed upto 800 meters/min and for hybrid yarn it can go up to 200 meters/min. To study the effect of parameter three variable namely Air pressure, Overfeed and Take-up speed are take in to consideration and the Box-Behanken design is used for experimental setup. The hybrid yarn samples have been evaluated to investigate the influence of process variables the commingling characteristics of hybrid yarn viz. nip frequency; nip stability and nip regularity have also been studied. 'MINITAB' software is used for the analysis of test results. It was observed that effects of individual parameter as well as interaction effects are equally important in deciding final yarn quality. The structural analysis of hybrid yarn is done using SEM (Scanning electron microscope). To study the mixing behaviour of glass/polypropylene hybrid yarn three different methods have been used to prepare hybrid yarn viz. Friction spinning, hollow spindle wrapping, commingling. Its was clearly observed that commingled process gives better homogenous mixing of glass and polypropylene filaments compare to other two method. This yarn is used to make final laminate sample using hot press.
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Souid, Hajer, Amel Babay, Mehdi Sahnoun, and Morched Cheikrouhou. "A COMPARATIVE QUALITY OPTIMISATION BETWEEN RING SPUN AND SLUB YARNS BY USING DESIRABILITY FUNCTION." AUTEX Research Journal 8, no. 3 (2008): 72–76. http://dx.doi.org/10.1515/aut-2008-080303.
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Abstract The present study was conducted to develop a credible approach to determine the quality of ring spun and slub yarns by virtue of criteria incorporating combinations of the fundamental fiber characteristics. Critical yarn parameters are to be investigated. The values of these tested properties were introduced into a database that ranked the quality of the yarn against industry standards. The paper investigates the possibilities of using the global optimization superimposed diagram response surface methodology in order to identify the spinner feasibility conditions across the customer yarn quality requirements. The spinner approach consists of optimizing the yarn count and twist. We have also studied the customer approach to optimize the yarn responses simultaneously by the use of the desirability functions. The response optimizer searches for a combination of input variables that jointly optimize the set of the responses by satisfying the customer requirements for each response in the set.
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Smith, C. Wayne, Steve Hague, Eric Hequet, and Brendan Kelly. "Yarn Performance of Texas Quality Upland Cotton Germplasm." Journal of Cotton Science 25, no. 1 (2021): 21–30. http://dx.doi.org/10.56454/blry3877.
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Ring and rotor spinning predominate the cotton spinning market with ring spinning dominating globally while United States (U.S.) spinners prefer rotor because of its production speed and high automation level. Newer and faster spinning technologies such as “air jet” spinning, exemplified by Murata Vortex Spinning (MVS), are being deployed. Rotor spinning produces yarn five times faster than ring, and the MVS produces 100 % cotton yarn over 20 times faster than ring spinning. Fiber quality improvements will be necessary for Upland cotton to be competitive with other fibers on MVS. Texas A&M Agrilife Research has released improved fiber quality germplasm lines and cultivars that equal or exceed the fiber quality parameters associated with the New Mexico Acala germplasm pool, which is considered the elite quality among Upland breeding pools. Two improved quality Texas A&M germplasm lines were compared with Acala 1517-08 for High Volume Instrument (HVI) and Advanced Fiber Information System (AFIS) fiber quality parameters plus yarn strength and appearance parameters. These genotypes were grown in 2017 and 2019 at Weslaco, Texas under irrigated culture. The three genotypes were similar in all fiber quality measurements except lengh and fiber strength. TAM 06WE-621 and TAM KJ-Q14 produced stronger yarns with improved yarn appearance when spun on either ring or air jet spinning technologies. Data suggest that the Texas A&M quality germplasm pool can be used to develop Upland cotton cultivars that will produce fibers competitive for the emerging MVS technology.
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Ren, Jia Zhi, Guo Xin Jia, and Qing Guo Feng. "Research on Feed Processing Parameters of the Cotton Comber." Advanced Materials Research 291-294 (July 2011): 339–43. http://dx.doi.org/10.4028/www.scientific.net/amr.291-294.339.
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For combed spun yarn of high quality, the feed amount per cycle and the bat weight have to be chosen correctly. When the feed amount per cycle and the bat weight are too low or too great, there is an effect on the combing efficiency, piecing quality, percentage of noil and quality of spun yarn. The influence of the feed amount per cycle and the bat weigh on combing efficiency, percentage of noil and piecing quality are analyzed theoretically. In order to investigate the effects of the feed amount per cycle and the bat weight on yarn quality (unevenness CV%, thin places, thick places and neps), The 14.6 tex yarn is spun on combing spinning system with E62 comber. The results of our investigations reveal that high combing efficiency and high quality yarn can be obtained with a lesser feed amount per cycle and a bigger bat weight on new type of cotton comber.
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Sette, S., and L. van Langenhove. "OPTIMISING THE FIBRE-TO-YARN PRODUCTION PROCESS: FINDING A BLEND OF FIBRE QUALITIES TO CREATE AN OPTIMAL PRICE/QUALITY YARN." AUTEX Research Journal 2, no. 2 (2002): 57–63. http://dx.doi.org/10.1515/aut-2002-020201.
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Abstract An important aspect of the fibre-to-yarn production process is the quality and price of the resulting yarn. The yarn should have optimal product characteristics, while maintaining as low a price as possible. Early optimisation models of the fibre-to-yarn process, based on neural networks and genetic algorithms, were severely limited in their potential applications as they generated unrealistic (ideal) conditions for the process. In this paper, a method is presented to model and optimise the fibre-to-yarn production process which avoids the aforementioned problems. A neural network is used to model the process, with the machine settings and fibre quality parameters as input and yarn tenacity and elongation as output. A constrained optimisation algorithm is used afterwards to optimise the blend of fibre qualities to obtain the best yarns. This results in an optimal price-yarn quality surface where each point corresponds with a set of blend coefficients and machine settings. Furthermore, constraints can easily be adjusted to correspond to real-life production environments.
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Zhang, Yujing, Zhiguo Yang, Zhongwei Wang, Xing Li, and Zhuo Meng. "Yarn tension model and vibration analysis during unwinding of carbon fiber bobbins." Journal of Industrial Textiles 53 (January 2023): 152808372311789. http://dx.doi.org/10.1177/15280837231178944.
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A low-quality unwinding process of the unwinding machine can lead to downtime of the knitting machine and loss of fabric quality. To address this issue, we studied the tension and vibration of carbon fiber yarns during unwinding. Based on the theory of axially moving strings, the dynamic model of carbon fiber yarn was established during the unwinding process, bringing the parameters into the simulation. According to the simulation results, the yarn tension in the unwinding process is closely related to the spring preload, which needs control within a certain range. When the unwinding speed increases, the fluctuation amplitude, lateral vibration amplitude, and axial vibration amplitude of the yarn tension gradually increase, causing friction and wear of the carbon fiber yarn. By controlling factors such as spring preload, unwinding speed, and the number of bobbins unwound simultaneously, one can effectively control the yarn’s vibration and improve the quality of the yarn.
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Ray, Suchibrata, Anindya Ghosh, and Debamalya Banerjee. "Analyzing the effect of spinning process variables on blow room blended cotton melange yarn quality." Research Journal of Textile and Apparel 22, no. 1 (2018): 2–14. http://dx.doi.org/10.1108/rjta-05-2017-0019.
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Purpose The use and importance of mélange yarn in apparel sector is increasing day by day. With the gradual increase in market share, achieving the desired quality level of mélange yarn remains a challenge for yarn manufacturing industry. The purpose of this paper is to investigate the effect of raw material (dyed fiber percentage in the mixing), important spinning process variable (yarn twist multiplier) and productivity (spindle rpm of ring frame) on properties of cotton mélange spun yarn. Design/methodology/approach Box and Behnken Design of experiment has been used to investigate the important yarn quality parameters like evenness, imperfection, hairiness, breaking strength and breaking elongation of blow room blended cotton mélange yarn. The quadratic regression model is used to derive the statistical inferences about sensitivity of the yarn quality parameters to the different process variables. The response surfaces are constructed for depicting the geometric representation of yarn quality parameters plotted as a function of process variables. Findings The study shows that shade depth and spindle speed have significant effects on the mélange yarn unevenness and imperfections. Mélange yarn strength and hairiness are significantly affected by shade depth and yarn twist multiplier (TM). Yarn elongation at break is only influenced by the spindle speed. A darker shade is responsible for higher yarn unevenness, imperfection, hairiness and lower yarn strength. A higher spindle speed is also liable for deterioration of yarn quality. Practical implications Many spinning industries are planning to convert their existing spindles from normal gray yarn production to mélange yarn manufacturing. The outcome of this study will lead to achieve better mélange yarn quality and productivity by the industry. Originality/value Research on mélange yarn is itself scant. This study is exclusively conducted to analyze the individual and interactive effect of various process parameters on the mélange yarn quality.
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Bhortakke, M. K., T. Nishimura, T. Matsuo, Y. Inoue, and T. Morihashi. "High Speed Yarn Production with Air-Jet Spinning: Effects of Some Fiber Parameters." Textile Research Journal 67, no. 2 (1997): 101–8. http://dx.doi.org/10.1177/004051759706700205.
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This work is aimed at improving the quality of air-jet polyester/cotton blended yarns spun at a high delivery speed (285 m/min) and the fabrics produced from them. Short (28 mm) and fine (1.0 d) polyester fibers and combed cotton are used in an attempt to improve yarn strength and evenness. The possibility of increasing delivery speed when fine denier polyester is used is also investigated. Whereas fine polyester and combed cotton improve yarn strength, evenness, and imperfection level, short polyester fibers do not improve yarn evenness. Long polyester fibers improve a yarn's strength but lower its elongation, making it stiffer. Long, coarser polyester fibers and combed cotton lead to a higher number of long hairs. Fine polyester fibers increase the delivery speed without significant loss in yarn strength and evenness, but with a considerable deterioration in the yarn imperfection level and hairiness. Fabric abrasion resistance is higher for longer polyester and combed cotton fibers. While none of the variables influences fabric pilling resistance and compressional resilience, shorter polyester and carded cotton fibers promote higher compressional energy and reduce fabric thickness.
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HASSEN, MOHAMED BEN, MOHAMED TAHER HALIM, EMAD ABUALSAUOD, and ASEM OTHMAN. "Quality yarn index using AHP and Fuzzy method." Industria Textila 71, no. 05 (2020): 487–91. http://dx.doi.org/10.35530/it.071.05.1699.
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The yarn quality depends on many parameters: characteristics parameters, mechanical and physical properties. Making the hypothesis that the quality of the yarn is a multicriteria problem, in this paper, we propose a new method to determine the Quality Yarn Index QYI based on Analytic Hierarchy Process AHP and Fuzzy theory. A questionnaire was designed for experts of each field (weaving and knitting) to evaluate the relative importance for each property to determine coefficients of the AHP matrix. Results revealed that matrix coefficients changed with yarn application (weft or warp weaving and knitting) The QYI can be used in any application, where a rapid decision is needed, to evaluate the global quality of yarn and to make a comparison between different yarn qualities
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Hu, Zhenlong. "Prediction Model of Rotor Yarn Quality Based on CNN-LSTM." Journal of Sensors 2022 (August 8, 2022): 1–12. http://dx.doi.org/10.1155/2022/3955047.
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In the whole textile industry chain, yarn production is one of the key links, which has a great impact on the quality of textile and clothing products. For a long time, the textile industry has been hoping for a yarn quality prediction technology, which can accurately predict the final yarn quality indicators according to the known conditions such as raw materials and production processes. CNN-LSTM yarn prediction model is a deep neural network model based on the assumption that the influence of textile processing time series on yarn quality is considered. CNN optimizes the input eigenvalues through one-dimensional convolution and pooling, and LSTM matches the optimized fiber performance indexes and process parameters in time series according to the processing sequence and excavates their laws, thus realizing the goal of predicting yarn quality indexes. The effects of input fiber performance index, process parameters, convolution kernel parameters, pool kernel parameters, LSTM unit number, LSTM layer number, and optimization algorithm on prediction accuracy were studied, and the parameters of CNN-LSTM model were determined. Experiments on the data set of spinning yarn show that the mean square error (MSE) of CNN-LSTM model in predicting yarn strength, Dan Qiang unevenness, evenness unevenness, and total neps is lower than that of linear regression model and BP neural network. At the same time, it is found that the prediction accuracy of CNN-LSTM model is greatly influenced by process parameters and optimization algorithm.
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Pei, Zeguang, Xingbao Wang, Zhimin Li, Lei Xiao, Tao Bai, and Ge Chen. "Effect of process and nozzle structural parameters on the wrapping quality of core-spun yarns produced on a modified vortex spinning system." Textile Research Journal 91, no. 15-16 (2021): 1841–56. http://dx.doi.org/10.1177/0040517521989094.
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Vortex core-spun yarn containing a metal wire has a broad application prospect owing to the combination of its fasciated structure, durability, comfort, and its electrical properties. In this paper, three-dimensional numerical simulations on the flow characteristics inside the nozzle of a modified vortex spinning system for producing core-spun yarns are carried out to investigate the effect of some process and nozzle structural parameters—the nozzle pressure, distance between nozzle inlet and spindle, and protrusion length of the filament feeding tube—on the flow field. Using a machine vision system, experiments are also conducted to investigate the effects of these parameters on the wrapping defects of the vortex core-spun yarns which are then analyzed based on the simulation results. The number of wrapping defects on the yarn greatly decreases as the nozzle pressure increases from 4 × 105 Pa to 5 × 105 Pa. As the distance between nozzle inlet and spindle increases, the number of wrapping defects on the yarn first decreases and then increases. The effect of protrusion length of the filament feeding tube is found to be insignificant. This experimental and numerical study can provide a feasible way for optimizing the quality of the core-spun yarn produced on the modified vortex spinning system and analyzing the mechanism of the effects of parameters.
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Sette, S., L. Boullart, L. Van Langenhove, and P. Kiekens. "Optimizing the Fiber-to-Yarn Production Process with a Combined Neural Network/Genetic Algorithm Approach." Textile Research Journal 67, no. 2 (1997): 84–92. http://dx.doi.org/10.1177/004051759706700203.
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An important aspect of the fiber-to-yam production process is the quality of the resulting yarn. The yarn should have optimal product characteristics (and minimal faults). In theory, this objective can be realized using an optimization algorithm. The complexity of a fiber-to-yarn process is very high, however, and no mathematical function is known to exist that represents the whole process. This paper presents a method to simulate and optimize the fiber-to-yam production process using a neural network combined with a genetic algorithm. The neural network is used to model the process, with the machine settings and fiber quality parameters as input and the yarn tenacity and elongation as output. The genetic algorithm is used afterward to optimize the input parameters for obtaining the best yarns. Since this is a multi-objective optimization, the genetic algorithm is enforced with a sharing function and a Pareto optimization. The paper shows that simultaneous optimization of yarn qualities is easily achieved as a function of the necessary (optimal) input parameters, and that the results are considerably better than current manual machine intervention. The last part of the paper is dedicated to finding an optimal mixture of available fiber qualities based on the predictions of the genetic algorithm.
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Borah, R. R., and M. Saikia. "Effect of Ailanthus species and seasons on yarn parameters of eri silk." Environment Conservation Journal 23, no. 1&2 (2022): 15–21. http://dx.doi.org/10.36953/ecj.021850-2136.
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Present research entails an in-depth analysis on the effect of two secondary host plants of eri silkworm viz., borpat (Ailanthus grandis Prain) and borkesseru (Ailanthus excels Roxb.) and seasons on yarn parameters of eri silk as quality of silk depends on food quality and rearing season. Seasons had significant effect on all the yarn parameters viz., yarn size, breaking load, tenacity and elongation except twist per inch. Significantly the highest yarn size (10.26s) was observed in autumn season which was at par with the spring season. But the maximum breaking load (0.67 kg) and tenacity (1.40 g/denier) were recorded in spring season and elongation (26.54%) in early summer season. Regardless of the seasons, significantly the higher breaking load (0.64 kg) and tenacity (1.51 g/denier) were recorded on the borkesseru leaves. The interaction effect of seasons and two host plants on eri silk yarn was found to be non-significant. Diversiform effect of both the seasons and the host plants pertaining to yarn characters were witnessed. It can be ensured that all the seasons and host plants are relevant with slight alteration in the yarn quality.
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Singh, Sukhvir, Niranjan Bhowmick, and Anand Vaz. "Effect of can-storage parameters of finisher drawframe on combed ring spun yarn quality." Research Journal of Textile and Apparel 23, no. 2 (2019): 153–67. http://dx.doi.org/10.1108/rjta-06-2018-0040.
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Purpose The present work is a systematic study to understand the cause of poor quality of sliver, roving and yarn due to defective sliver storage can-spring at finisher drawframe machine in spinning preparatory. This study aims to investigate the influence of can-spring stiffness factor, sliver deposition rate and sliver coils position on yarn unevenness and thin places considering two cases of sliver storage time. Design/methodology/approach Combed ring spun yarn samples were produced by varying finisher drawframe variables, which were can-spring stiffness, delivery speed and sliver coils position in storage can. For research design, three-factor three levels of Box-Behnken experimental design was adopted. To investigate the effect of sliver storage time on combed yarn unevenness and thin places, yarn samples were produced at 8 h sliver storage time and without allowing any storage time. Sliver storage time is the time for which combed drawn sliver kept idle in storage cans before feeding to speedframe machine. The 8 h sliver storage time was considered for present study after consulting industrial experts. Adequate numbers of the samples were tested for yarn quality parameters such as yarn unevenness and thin places 50 per cent/km on standard instruments. Finally, the test results were analyzed using statistical software to check the statistical significance of all the independent variables on observed response through analysis of variance. Findings The experimental results showed that the yarn samples produced from older can-springs and bottom position sliver coils stored at 8 h storage time were showing higher yarn unevenness and thin places compared to other yarn samples. The results also showed that the effect of delivery speed is not significant on yarn unevenness for samples produced without allowing any sliver storage time. Research limitations/implications The present study is an outcome of a practical problem experienced at the finisher drawframe machine in a spinning industry. For this purpose, only scrutinized finisher drawframe variables were considered for the evaluation. There are many equally important other factors, which were not considered due to research work feasibility. Social implications This paper investigates the effect of some imperative factors at the finisher drawframe stage on combed yarn quality. The present study will boost existing knowledge of the spinner’s community regarding the effect of can-spring stiffness, sliver coils position and storage time on resultant combed yarn quality parameters. Originality/value The work is original and only a few references are available. The study reveals that storage can-spring stiffness should be chosen carefully for better sliver handling. It is observed that finisher drawframe can-spring stiffness, sliver storage time and sliver coils position play a vital role in deciding quality characteristics of stored sliver and ultimately affect yarn quality.
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Yilmaz, Demet, and Mustafa Resit Usal. "Effect of Nozzle Structural Parameters on Hairiness of Compact-Jet Yarns." Journal of Engineered Fibers and Fabrics 7, no. 2 (2012): 155892501200700. http://dx.doi.org/10.1177/155892501200700209.
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Hairiness significantly influences the appearance of yarns and fabrics. New methods and spinning systems have been offered to reduce it. Nevertheless, there is still the quest for easy, low-cost processes to produce good quality yarns with reduced hairiness. Therefore, due to its considerable importance for spun yarns, we worked on a new spinning method to decrease yarn hairiness. Many researchers have been studying the use of air nozzles in the spinning and also the winding processes, and they indicated that hairiness decreases by up to 40–50%. From this point, we investigated the use of an air nozzle on a compact spinning system and discussed the effect on yarn hairiness. The nozzle was positioned at the exit of the drafting system on a RoCoS compact spinning system and pressurized air was fed into the nozzle by the compressor during spinning. We called the combination of an air nozzle and a compact spinning system a Compact-Jet spinning system. In the literature, there are no such trials. At the end of the study, it was determined that a Compact-Jet spinning system truly improves hairiness by up to 40% in comparison to the compact spinning system and by up to 70% compared with the conventional ring spinning system. Regarding the nozzle structural parameters, the changes in hairiness indicate that the main hole diameter and nozzle outlet design make the most important contributions in reducing yarn hairiness; whereas the injector angle and nozzle head type show weaker effects. As a result, the Compact-Jet can be considered as an innovative spinning system providing the opportunity to produce less hairy yarn. Additionally, we believe that this study makes an important contribution to the research activities in the spinning field and its associated literature.
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Umair, Muhammad, Khubab Shaker, Yasir Nawab, Abher Rasheed, and Sheraz Ahmad. "A Study on the Twist Loss in Weft Yarn during Air Jet Weaving." Journal of Engineered Fibers and Fabrics 12, no. 4 (2017): 155892501701200. http://dx.doi.org/10.1177/155892501701200401.
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Air jet weaving is considered to be the most advanced method of fabric production in which weft yarn is inserted with air pressure. But due to very high pressure some of yarn twist is lost during fabric production. This affects the strength of the yarn in general and quality of the fabric in particular. This study deals with the parameters affecting twist loss in weft yarn during air jet weaving. The subsequent effect of twist loss on the mechanical properties of yarn as well as fabric is also studied. A total of twenty-four different fabric samples were produced to consider the effect of yarn linear density, material, weave design and fabric width on the twist loss in picking and receiving sides of the woven fabric. The 100% cotton and polyester-cotton (PC) ring spun yarns having linear densities 37, 27 and 15 tex were used to produce fabrics in two different weaves i.e. 1/1 plain and 3/1 twill weave. In addition, two different fabric widths i.e. 121 and 100 cm were produced. The twist loss increases with increase in the fineness of yarn. In PC yarns twist loss percentage was higher as compared to cotton yarns. Twist loss in wider width was higher as compared to smaller widths of the fabric, while the effect of weave design was negligible.
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Das, B. R. "Tensile Behaviour of Spun Yarns under Static State." Journal of Engineered Fibers and Fabrics 5, no. 1 (2010): 155892501000500. http://dx.doi.org/10.1177/155892501000500101.
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The tensile properties of spun yarn are accepted as one of the most important parameters for assessment of yarn quality. The tensile properties decide the performance of post spinning operations; warping, weaving and knitting and the properties of the final textile structure; hence its accurate technical evaluation carries much importance in industrial applications. There is no doubt that all the studies related to tensile behaviour of spun yarns are invaluable both in theory and practice. In this article, a critical review of the theoretical and practical aspect of static tensile behaviour of staple yarns has been discussed.
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Cui, Yuemin, Hong Song, Longdi Cheng, Wansheng Deng, and Yijun Ji. "Experimental study of a modified drafting system based on the ring spinning frame." Textile Research Journal 91, no. 13-14 (2021): 1486–96. http://dx.doi.org/10.1177/0040517520984977.
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A systematic study of a modified drafting system based on the ring spinning frame, which is called the SDS (soft drafting system), is reported in this article to raise yarn quality. Two parts of an experiment were conducted to investigate differences between the conventional and modified drafting systems by spinning three kinds of yarns (in part I) and the effects of process parameters (block gauge, pressure on the front rollers and break draft) on the SDS by using response surface methodology (RSM) to spin 18.2 tex cotton yarn (in part II). The results show that the SDS can significantly improve yarn evenness and reduce yarn imperfections of thick places by +35% and +50%, respectively, and neps by +140% per km. In addition, it is noted that the three parameters are all statistically significant for the SDS to spin yarns, while interactions between them are not. More importantly, RSM predicted a minimum CVm% of 13.95% under the optimum conditions of 1.75 mm, 190 N and 1.21 for the block gauge, pressure on the front rollers and break draft, respectively, which is very close to the conditions of the practical spinning test.
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Ferede, Eyasu, Tamrat Tesfaye, Million Ayele, Desalegn Atalie, and Bewuket Teshome Wagaye. "Prediction of the Impact of Ring Spinning Machine Front Roller Rubber Cot Shore Hardness on Spun Yarn Quality Parameters." Textile & Leather Review 7 (January 5, 2024): 18–34. http://dx.doi.org/10.31881/tlr.2023.157.
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The yarn quality is mostly determined by the spinning settings, process control methods, and raw material. The most crucial and fundamental process in ring spinning is drafting, which has a significant impact on the quality of the yarn. Yarn quality is greatly impacted by drafting elements such as shore hardness. This study aimed to predict the effect of different degrees of shore hardness in the ring machine front roller rubber cot on 100% cotton and 32s Ne ring spun yarn quality parameters. The backline shore hardness was constant. Cotton yarn properties, including mass uniformity, imperfection level, unevenness, hairiness, tensile strength, and elongation, were measured and analyzed in accordance with ASTM D1425-96 and ASTM D2256, 2015 test standards, respectively. Linear regression equations were developed for prediction. A linear regression analysis showed that there is a positive correlation between shore hardness and yarn quality parameters with higher R2 values. Therefore, almost in all cases, the value of R2 was above 0.834, which signifies one can make a definite prediction about the yarn properties with different shore hardness. From the result of this study, it can be concluded that the quality of the produced yarn is superior to about 63-65° shore hardness values.
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G., K. Tyagi Ashvani Goyal and Sushant Dhiman. "Optimizing Speed Frame Drafting Variables for Yarn Uniformity and Hairiness Using Taguchi Design." Journal Of The Textile Association (JTA) 85, no. 5 (2025): 1–10. https://doi.org/10.5281/zenodo.14973747.
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Background: The drafting system configuration in speed frames significantly influences the quality ofspun yarn. Factors such as yarn irregularity, coefficient of variation (CV %), imperfections, and hairinessare crucial parameters for evaluating yarn quality. This study compares the performance of PK 1500and PK 1600 drafting systems with 3-over-3 and 4-over-4 configurations using Taguchi methods tooptimize drafting variables for better yarn uniformity and reduced hairiness.Methodology: The study analyzed the effects of front and back top roller pressure, spacer size, andoverhang in the drafting region for PK 1500 (3/3 and 4/4) and PK 1600 (4/4) systems. Taguchi designand analysis of variance (ANOVA) were employed to evaluate the impact of these variables on yarnproperties, including irregularity, CV%, imperfections, and hairiness.Results: The 3-over-3 configuration of the PK 1500 drafting system outperformed the 4-over-4 setups inproducing yarn with lower unevenness, reduced CV%, and fewer imperfections. Additionally, thehairiness was found to be significantly higher in yarns produced with the 4-over-4 configurations of bothPK 1500 and PK 1600 systems.Conclusion: The study concluded that the 3-over-3 drafting system in the PK 1500 configuration offerssuperior yarn quality for the tested material and machine settings. This configuration is recommendedfor achieving optimal yarn uniformity and minimized hairiness, highlighting its advantages over 4-over4 setups.
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Bhowmick, Manik, Arup Kumar Rakshit, and Sajal Kumar Chattopadhyay. "Dref-3 yarn structure with plied staple fibrous core." Research Journal of Textile and Apparel 22, no. 3 (2018): 235–46. http://dx.doi.org/10.1108/rjta-09-2017-0044.
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Purpose Dref-3 friction spun core yarns produced using staple fibre yarn as the core, e.g. Jute core yarn wrapped with cotton fibre, have poorer mechanical properties compared to the core yarn itself. The purpose of this study was to understand the structure of such yarns, that will lead to the optimization of fibre, machine and process variables for production of better quality yarn from the Dref-3/3000 machines. Design/methodology/approach The Dref spinning trials were conducted following a full factorial design with six variables, all with two operative levels. The Dref-3 friction spun yarn, in which the core is a plied, twisted ring yarn composed of cotton singles and the sheath, formed from the same cotton fibres making the singles, has been examined. The structures have also been studied by using the tracer fibre technique. Findings It was observed that rather than depending on the plied core yarn, the tensile properties of the Dref-3 yarn are significantly determined by the parameters those affect the constituent single yarn tensile properties, i.e. the amount of twist and its twist direction, yarn linear density and the sheath fibre proportion used during the Dref spinning in making the final yarn. Further, when the twist direction of single yarn, double yarn and the Dref spinning false twisting are in the same direction, the produced core-sheath yarn exhibits better tensile properties. Practical implications The understanding of the yarn structure will lead to optimized production of all staple fibre core Dref spun yarns. Social implications The research work may lead to utilization of coarse and harsh untapped natural fibres to the production of value-added textile products. Originality/value Though an earlier research has reported the effects of sheath fibre fineness and length on the tensile and bending properties of Dref-3 friction yarn, the present study is the first documented attempt using the tracer fibre technique to understand Dref-3 yarn structure with plied staple fibrous core.
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Pereira, Filipe, Alexandre Macedo, Leandro Pinto, et al. "Intelligent Computer Vision System for Analysis and Characterization of Yarn Quality." Electronics 12, no. 1 (2023): 236. http://dx.doi.org/10.3390/electronics12010236.
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The quality of yarn is essential in the control of the fabrics processes. There is some commercial equipment that measures the quality of yarn based on sensors, of different types, used for collecting data about some textile yarn characteristic parameters. The irregularity of the textile thread influences its physical properties/characteristics and there may be a possibility of a break in the textile thread during the fabric manufacturing process. This can contribute to the occurrence of unwanted patterns in fabrics that deteriorate their quality. The existing equipment, for the above-mentioned purpose, is characterized by its high size and cost, and for allowing the analysis of only few yarn quality parameters. The main findings/results of the study are the yarn analysis method as well as the developed algorithm, which allows the analysis of defects in a more precise way. Thus, this paper presents the development and results obtained with the design of a mechatronic prototype integrating a computer vision system that allows, among other parameters, the analysis and classification, in real time, of the hairs of the yarn using artificial intelligence techniques. The system also determines other characteristics inherent to the yarn quality analysis, such as: linear mass, diameter, volume, twist orientation, twist step, average mass deviation, coefficient of variation, hairiness coefficient, average hairiness deviation, and standard hairiness deviation, as well as performing spectral analysis. A comparison of the obtained results with the designed system and a commercial equipment was performed validating the undertaken methodology.
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Ghanmi, Hanen, Adel Ghith, and Tarek Benameur. "Ring yarn quality prediction using hybrid artificial neural network." International Journal of Clothing Science and Technology 27, no. 6 (2015): 940–56. http://dx.doi.org/10.1108/ijcst-01-2015-0015.
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Purpose – The purpose of this paper is to predict a global quality index of a ring spun yarn whose count Ne is ranging between 7.8 (76.92 tex) and 22.2 (27 tex). To fulfill this goal, a hybrid model based on artificial neural network (ANN) and fuzzy logic has been established. Fiber properties, yarn count and twist level are used as inputs to train the hybrid model and the output would be a quality index which includes the major physical properties of ring spun yarn. Design/methodology/approach – The hybrid model has been developed by means of the application of two soft computing approaches. These techniques are ANN which allows the authors to predict four important yarn properties, namely: tenacity, breaking elongation, unevenness and hairiness and fuzzy expert system which investigates spinner experience to give each combination of the four yarn properties an index ranging from 0 to 1. The prediction of the model accuracy was estimated using statistical performance criteria. These criteria are correlation coefficient, root mean square error, mean absolute error and mean relative percent error. Findings – The obtained results show that the constructed hybrid model is able to predict yarn quality from the chosen input variables with a reasonable degree of accuracy. Originality/value – Until now, there is no sufficiently information to evaluate and predict the global yarn quality from raw materials characteristics and process parameters. Therefore, this present paper’s aim is to investigate spinner experience and their understanding about both the impact of various parameters on yarn properties and the relationship between these properties and the global yarn quality to predict a quality index.
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Lang, Tobias Georg, Mir Mohammad Badrul Hasan, Anwar Abdkader, Chokri Cherif, and Thomas Gereke. "Micromechanical Modelling of the Deformation Mechanisms of Friction-Spun Yarn from Recycled Carbon Fibres." Materials Science Forum 1117 (March 19, 2024): 47–53. http://dx.doi.org/10.4028/p-atiih0.
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The growing use of carbon fibre-reinforced polymers (CFRP) results in an increased amount of CF waste from offcuts or end-of-life components. A promising method to reuse the waste fibre materials in a structural component with excellent mechanical properties is the processing of recycled CF (rCF) and thermoplastic fibres into hybrid yarns. Spinning of friction spun yarns consisting of more than 90% rCF and containing almost no thermoplastic fibres that are suitable for thermoset composites, currently leads to high fibre damage and low yarn quality and is, therefore, addressed in this project. The technology is reported in another paper. One of the limiting factors for drapability of textiles is the stretchability of continuous fibres and draping of the semi-finished textile products for complex geometries is still error-prone. Friction spun yarns exhibit significantly higher yarn elongations due to sliding mechanisms between the fibres. The deformation properties of friction spun yarns are significantly influenced by fibre-fibre interactions and depend on a variety of process and material parameters. In the following, micromechanical finite element models of the spun yarns are created by using beam elements. Monte Carlo method is used to model local variabilities in the yarns. The models are then used to simulate yarn behaviour under deformation and to investigate the influence of various process parameters.
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Zhang, Ru Quan, Jian Qiang Li, Yu He, and Hui Jiang. "Prediction of Yarn Quality by Support Vector Machine." Advanced Materials Research 503-504 (April 2012): 1429–32. http://dx.doi.org/10.4028/www.scientific.net/amr.503-504.1429.
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For the prediction of yarn quality, this paper presents method to predict the quality of the spinning by a support vector machine. The input parameters to support vector machines including density of coarse yarn, roving twist factor, yarn linear density, yarn twist factor , the output variable is the CV values of spinning, breaking strength, establishment prediction model of CV values, breaking strength SVM. The results showed that: 11 groups of training samples randomly selected from 13 groups samples, two groups as predict sample, forecast errors are below 5% with high accuracy. This research provides a new approach for the spinning process design and quality control.
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Teklehaimanot, Mebrahtom, Kiday Fisseha, and Million Ayele. "Combined Effect of Carding Machine Process Parameters on Yarn Properties; Process Optimization." TEKSTILEC 65, no. 1 (2022): 58–66. http://dx.doi.org/10.14502/tekstilec.65.2021020.
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Yarn tensile properties, unevenness, and irregularities are the most important properties of the yarn quality parameters that determine the fabric’s mechanical properties and appearance. In the current study, the combined effect of carding machine parameters (cylinder speed, flat speed, cylinder to flat setting, and taker-in speed) on yarn properties (yarn strength, elongation, unevenness, and total yarn imperfection) have been examined. In this research, 40 samples of open-end yarn were produced and each of them was tested for their strength, elongation, unevenness, and imperfection. Design-expert 7.0.0 software and Factorial designing have been employed to analyze the results. The results from statistical analysis have showed that increasing the gap between the cylinder and flat setting and increasing the taker-in speed increased yarn unevenness and increasing cylinder speed, flat speed, and taker-in speed increased total yarn imperfection significantly. Similarly, increasing the flat speed, cylinder speed, and taker-in speed as well as increasing the gap between the cylinder and flat reduced yarn strength and elongation significantly.
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Ashraful Alam, Zakaria Ahmed, Neaz Morshed, Pulak Talukder, and Taslima Rahman. "Research on reduction of yarn co-efficient of variation percentage and imperfection from auto-cone yarn." International Journal of Scientific Research Updates 4, no. 2 (2022): 160–64. http://dx.doi.org/10.53430/ijsru.2022.4.2.0176.
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It’s been a problem over the years that auto cone produces more imperfection and co-efficient of variation (CV) percentage than ring yarn. It was found that lowering the gauge from the running setting results for better quality yarn (less CV% and imperfection) without affecting any other parameters related with production. Thus, it can clearly be stated that less yarn clearer gauge results for better quality yarn.
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Hasani, Hossein, Somayeh Akhavan Tabatabaei, and Ghafour Amiri. "Grey Relational Analysis to Determine the Optimum Process Parameters for Open-End Spinning Yarns." Journal of Engineered Fibers and Fabrics 7, no. 2 (2012): 155892501200700. http://dx.doi.org/10.1177/155892501200700212.
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This article focuses on an approach based on the Taguchi method with grey relational analysis for optimizing the process parameters for open-end spun yarns with multiple performance characteristics. A grey relational grade obtained from the grey relational analysis is used to optimize the process parameters. Optimal process parameters can then be determined by the Taguchi method using the grey relational grade as the performance index. CVm%, hair number per meter, and tenacity of yarn were selected as quality characteristics. Using these characteristics, the process parameters, including rotor speed, rotor diameter, opener speed, yarn linear density and navel type are optimized. The raw materials used in this investigation were cotton fibers (35%) and cotton waste (65%) collected from ginning machines. The Experimental results show parameter rotor speed has the most significant effect on the multiple performance characteristics.
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Yang, Shouren, and Stuart Gordon. "Accurate prediction of cotton ring-spun yarn quality from high-volume instrument and mill processing data." Textile Research Journal 87, no. 9 (2016): 1025–39. http://dx.doi.org/10.1177/0040517516646051.
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The derivation and performance of yarn quality prediction models in a program called Cottonspec is reported. Cottonspec incorporates a large database of fiber and yarn data from commercial spinning mills, a series of regression-based models predicting yarn quality from measured cotton fiber quality parameters and yarn specifications and a user interface. The inclusion of independent variables into prediction equations was dependent on the criteria that their inclusion was statistically significant and that variables had a theoretically direct influence on yarn structure. Yarn data was corrected to allow for twist, yarn count and yarn irregularity before correlation with fiber properties. Differences in yarn testing results between mills could be corrected by a Mill Correction Factor. Adherence to these criteria and the ability to draw on the very large database meant prediction ability of the models was excellent, as demonstrated in a series of cross-validations.
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Mirzabaev, B. B., N. Yu Sharibaev, and S. S. Sharipbaev. "MOISTURE ABSORPTION CHARACTERISTICS OF YARNS IN VARIOUS ENVIRONMENTS." American Journal of Engineering and Technology 6, no. 12 (2024): 181–89. https://doi.org/10.37547/tajet/volume06issue12-17.
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This article examines the capacity of yarns to absorb moisture under different environmental conditions. The study focuses on yarn structure, moisture absorption and retention properties, and the influence of environmental factors such as temperature, relative humidity, and pressure. The article delves into the mechanism of moisture absorption in yarns and explores ways to optimize these parameters. The findings are significant for enhancing productivity and improving product quality in the textile industry.
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Jabbar, Abdul, Tanveer Hussain, and Abdul Moqeet. "Impact of Carding Parameters and Draw Frame Doubling on the Properties of Ring Spun Yarn." Journal of Engineered Fibers and Fabrics 8, no. 2 (2013): 155892501300800. http://dx.doi.org/10.1177/155892501300800209.
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The impact of card cylinder speed, card production rate and draw frame doubling on cotton yarn quality parameters was investigated by using the Box-Behnken experimental design. It was found that yarn tenacity, elongation and hairiness increase by increasing the number of draw frame doubling up to a certain level and then decrease by further increase in doubling. Yarn unevenness increased by increasing card production rate and total yarn imperfections increased by decreasing card cylinder speed and increasing card production rate.
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Krupincová, G., and J. Hatipoglu. "Testing of yarn abrasion." Autex Research Journal 13, no. 1 (2013): 22–27. http://dx.doi.org/10.2478/v10304-012-0019-3.
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Abstract There exist a lot of methodologies, which can be used for yarn quality testing. Abrasion resistance and its measurement for raw and sized yarn can help in the judgment of yarn weaving-ability. This article concentrates on the possibility of yarn abrasion expression and testing. Relation among fiber material characteristics, selected yarn structural, and mechanical parameters is discussed and a few experimental results are shown.
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Sayed, Md Abu, Md Bashar Uddin, and Hosne Ara Begum. "Comparative Study of Cotton Yarn Properties Using Central-Fan and Multi-Fan for Vacuum Generation in Aerodynamic Compact Spinning Systems." Textile & Leather Review 5 (June 28, 2022): 240–52. http://dx.doi.org/10.31881/tlr.2022.28.
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Today, aerodynamic compact spinning is the most widely used compact spinning method in which the vacuum (negative pressure airflow) is generated to compact the fibre strands. Different manufacturers use different vacuum generation systems, which can be divided into the following – a central fan system with combined duct and independent duct and a multiple fan system. The information on each system and its impact on yarn properties would be quite attractive for research. This empirical study investigated the properties of yarns manufactured on the aerodynamic compact spinning systems with widely-used different vacuum systems. To preserve neutrality, these systems were referred to as CFS (CDS and IDS) and MFS instead of using their commercial names. It was found that CFS was the most remarkable concerning yarn irregularity (U% and CVm%), imperfection index (IPI), and bundle yarn strength (CSP) in comparison with the MFS. Though the yarn hairiness in MFS was better than in IDS, overall quality parameters were not as comparable to IDS or CDS.
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Yang, Jian Guo, Lan Xu, Zhi Jun Lu, Qian Xiang, and Bin Liu. "Yarn Quality Prediction and Process Parameters Optimization Based on Genetic Algorithm and Neural Network." Applied Mechanics and Materials 742 (March 2015): 377–83. http://dx.doi.org/10.4028/www.scientific.net/amm.742.377.
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Quality prediction is an important means of the quality management in modern spinning production. This paper proposed a yarn quality prediction model based on Genetic Algorithm and back propagation neural network to predict the yarn quality and optimize the process parameters. The main identification model parameters were optimized by using genetic algorithm, and the prediction performance of the model has been compared against that of the BP neural network model. The effectiveness and availability of the proposed model are verified with the use of actual production data.
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Lan, Wei-Lun, and Chung-Feng Jeffrey Kuo. "Development of a warming multi-functional fabric Part I: The analytic hierarchy process combined with the technique for order preference by similarity to an ideal solution for the optimization of the multi-quality melt spinning parameters in far-infrared functional yarn." Textile Research Journal 89, no. 11 (2018): 2247–59. http://dx.doi.org/10.1177/0040517518790972.
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This series study develops a multi-functional yarn with far-infrared emission, heating, and antistatic properties for winter clothing. In Part I, polyethylene terephthalate (PET) is used as the polymer matrix, and nano germanium powder is uniformly mixed with PET by the melt blending process for modification, in order that the PET composite has far-infrared function. Afterwards, the modified PET is made into 75d/72f fully drawn yarn (FDY) by melt spinning and melt drafting. The properties of the yarn, including tensile strength, elongation at break, yarn count (in denier), far-infrared emissivity, and far-infrared heating are discussed. In order to optimize the quality of yarn in the melt spinning process, this study designs process parameters consisting of germanium powder addition, melt temperature, mold temperature, nozzle temperature, gear pump speed, and take-up speed using the Taguchi method. Then, the analytic hierarchy process (AHP) is applied to obtain the weights of each quality, which will be used in the technique for order preference by similarity to an ideal solution (TOPSIS) to obtain the optimal processing parameters for multi-quality yarn. The results show that the tensile strength of the optimized modification PET yarn is 4.84 g/d, the elongation at break is 41.26%, yarn count is 74.39d/72f, the far-infrared emissivity is 89% and the far-infrared heating is 6.3℃. The properties of the optimized modified yarn are obviously better than general PET yarn.
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Khurshid, Furqan, Sarmad Aslam, Usman Ali, Amir Abbas, Talha Ali Hamdani, and Fiaz Hussain. "Optimization of Break Draft, Pin Spacer and Rubber Cots Hardness to Enhance the Quality of Ring Spun Yarn Using Factorial Design." Journal of Engineered Fibers and Fabrics 13, no. 2 (2018): 155892501801300. http://dx.doi.org/10.1177/155892501801300209.
Full textAbstract:
The aim of the present work is to optimize the drafting parameters for ring spinning by using full factorial (23) experimental design. Three drafting parameters of ring spinning each at two levels were chosen for this study. These technological parameters were break draft, size of pin spacer and hardness of rubber cots. It was found from statistical analysis that pin spacer size has a significant effect on yarn unevenness (U %), imperfection index (IPI), hairiness (H) and yarn strength (CLSP) compared to the other two chosen factors. These yarn quality parameters were improved by increasing the spacer size. The increase in spacer size reduces the cohesive forces among the fibers during drafting. The pin between the cradle and the top front roller transfer the individual fibers from the drafted fiber assembly to the spinning triangle without any stretching or accumulation. This yields a more integrated structure and the quality of yarn is improved.
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Matismailov, S. L., K. R. Matmuratova, A. T. Yuldashev, N. A. Khusanova, and Sherzod Korabayev. "Features of the technology for producing combed yarn from medium-fiber cotton." BIO Web of Conferences 130 (2024): 01005. http://dx.doi.org/10.1051/bioconf/202413001005.
Full textAbstract:
The article examines the features of the technology of production of re-combed yarn from medium fiber cotton selection varieties. The experiments were carried out under production conditions on the Rieter E-66 combing machine. To determine the optimal technological parameters of the machine, a full factorial experiment was conducted to determine the unevenness of the 1-meter-long braid, the output of recombing tension, the staple length of the fibers in the strand, and regression equations were obtained. According to the results of the full-factor experiment, the improvement of the quality parameters of the recombing machine was achieved when the speed of the comb drum of the combing machine is 400 min-1, the distance between the lower jaw of the clamps and the comb segment is 0.2 mm, and the distance between the lower jaw of the clamps and the separating cylinder is 16.5 mm. According to the theoretical and experimental evaluations, using the optimal parameters of the high-speed combing machine, the cotton re-combed from the cotton fibers meeting all requirements was produced on the G-3 warped spinning machine of the Rieter company, with a drawing density of 14.8 tex (Ne 36). As a result of improving the physical and mechanical quality of spun yarn, the number of yarn breaks that damage 1000 yarns has decreased by 25%, and machine productivity has increased.