INfluence of Some Mechanical Factors of Ring Spinning Machine on Cotton Yarn Quality

2002 ◽  
Vol 2 (4) ◽  
pp. 453-456 ◽  
Author(s):  
Iftikhar Ahmad . ◽  
Nisar Ahmad Jamil . ◽  
Nadeem Haider .
Keyword(s):  
Cotton Yarn ◽  
Ring Spinning ◽  
Yarn Quality ◽  
Mechanical Factors

scholarly journals An adhesive-aided ring spinning for improving cotton yarn quality with the aid of sodium carboxymethyl cellulose solution

2020 ◽  
Vol 15 ◽  
pp. 155892502092783
Author(s):  
Peiying Li ◽  
Mingrui Guo ◽  
Fengxin Sun ◽  
Weidong Gao
Keyword(s):  
Carboxymethyl Cellulose ◽  
Sodium Carboxymethyl Cellulose ◽  
Surface Velocity ◽  
Speed Ratio ◽  
Cotton Yarn ◽  
Cellulose Solution ◽  
Ring Spinning ◽  
Yarn Quality ◽  
Yarn Hairiness ◽  
Cellulose Concentration

An adhesive-aided ring spinning was developed to improve cotton yarn quality through the wetting and adhesion effect of an adhesive solution, namely, sodium carboxymethyl cellulose solution on fibrous strand in yarn formation zone during spinning process. The spinning mechanism of the adhesive-aided ring spinning with sodium carboxymethyl cellulose solution was analyzed, and the effects of two factors, that is, speed ratio (the ratio of the linear surface velocity to the output speed) and sodium carboxymethyl cellulose concentration, on the yarn performance are investigated. The experiment results reveal that the adhesive-aided ring spinning with sodium carboxymethyl cellulose concentration of 0.7% can significantly reduce yarn hairiness indicated by the hairiness S3 value reducing to 69% and still showing a prominent reduction (65%) after winding process. It has been found that a slightly faster linear surface velocity of the cylinder of the adhesive-aided ring spinning compared with the output speed of the yarn is more beneficial to the reduction of yarn hairiness S1+2 value. Meanwhile, the higher sodium carboxymethyl cellulose concentration also contributes to a higher breaking strength (increasing from 18.24 to 21.12 cN/tex) and lower breaking elongation (reducing from 4.98% to 4.08%). The abrasion resistance of adhesive-aided ring spun yarns also shows an obvious improvement of 12.8%. Therefore, the newly developed adhesive-aided ring spinning with the sodium carboxymethyl cellulose solution provides an effective method to enhance the quality of cotton yarns.

Experimental study of a modified drafting system based on the ring spinning frame

2021 ◽  
pp. 004051752098497
Author(s):  
Yuemin Cui ◽  
Hong Song ◽  
Longdi Cheng ◽  
Wansheng Deng ◽  
Yijun Ji
Keyword(s):  
Experimental Study ◽  
Response Surface Methodology ◽  
Process Parameters ◽  
Systematic Study ◽  
Cotton Yarn ◽  
Optimum Conditions ◽  
Ring Spinning ◽  
Yarn Quality ◽  
Gauge Pressure ◽  
Block Gauge

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.

Prediction of Breaking Elongation of Polyester/Cotton Yarn in Ring Spun Processing

2011 ◽  
Vol 366 ◽  
pp. 108-112
Author(s):  
Bo Zhao
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Artificial Neural Network Model ◽  
Cotton Yarn ◽  
Ring Spinning ◽  
Breaking Elongation ◽  
Artificial Neural ◽  
Actual Test

The artificial neural network model is used to predict the breaking elongation of polyester/cotton ring spinning yarn in this paper. In order to achieve the objective, a series of trials is conducted. The prediction values and actual test values of which are found to be rather close. Therefore, the artificial neural network model proves to be more feasible in the prediction of breaking elongation of polyester/cotton ring spinning yarn.

scholarly journals Impact of Carding Parameters and Draw Frame Doubling on the Properties of Ring Spun Yarn

2013 ◽  
Vol 8 (2) ◽  
pp. 155892501300800 ◽  
Author(s):  
Abdul Jabbar ◽  
Tanveer Hussain ◽  
Abdul Moqeet
Keyword(s):  
Experimental Design ◽  
Production Rate ◽  
Quality Parameters ◽  
Cotton Yarn ◽  
Yarn Quality ◽  
Spun Yarn ◽  
Ring Spun Yarn ◽  
Yarn Tenacity ◽  
The Impact

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.

A Study on Growth and Financial Performance of Selected Textile Companies in Coimbatore District

1970 ◽  
Vol 3 (2) ◽  
pp. 101-111
Author(s):  
P. Chellasamy ◽  
N. Sumathi
Keyword(s):  
Driving Force ◽  
Garment Industry ◽  
Cotton Yarn ◽  
Remarkable Improvement ◽  
Yarn Quality ◽  
Coimbatore District ◽  
The World ◽  
Cotton Yarns ◽  
Yarn Production

The textile and garment industry fulfils a pivotal role in the Indian economy. It is a major foreign exchange earner and, after agriculture, it is the largest employer with a total workforce of 35 mn. In 2005 textiles and garments accounted for about 14% of industrial production and 16% of export earnings. In cotton yarn production India has made a mark in the world textile scenario. It is the largest exporter of the cotton yarns in the world. Besides yarn exports, India’s growing garment industry is working as a driving force to improve the yarn quality and to increase the production of cotton yarn. This has resulted in an overall improvement in the quality of all textile products including yarn and fabric. The WTO era has seen remarkable improvement in export of textiles. To help the mills in bench marking, SITRA has conducted a survey on the cotton yarn quality for fine and superfine yarns, in which 58 mills from all over India have taken part.

Numerical simulation of top roller pressure and deformation in ring spinning with three draft zones using finite element method

2016 ◽  
Vol 28 (2) ◽  
Author(s):  
Xiaojuan Zhang ◽  
Juan Wu ◽  
Bojun Xu ◽  
Xinjin Liu
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Carbon Fiber ◽  
Design Methodology ◽  
Ring Spinning ◽  
Ansys Software ◽  
Yarn Quality ◽  
Cotton Yarns ◽  
Yarn Tenacity ◽  
Element Method

Purpose This paper presented a new kind of ring spinning frame with four pairs of rollers, and they are the front roller and the front top roller, the first middle roller (FMR) and the first middle top roller (FMTR), the second middle roller and the second middle top roller, the back roller and the back top roller. The FMR is the front roller of middle draft zone, and the back roller of the front draft zone. Therefore, the deformation of FMTR during spinning is an important factor for yarn quality, which was studied in this paper. Design/methodology/approach In this paper, by finite element method (FEM), the pressure and deformation of FMTR were studied. FMTR made from steel and sleeved carbon fiber were compared. 5.8tex, 4.9tex and 3.9tex cotton yarns were spun, and corresponding numerical simulations of FMTR pressure and deformation were presented in ANSYS software and comparatively analyzed. Then, corresponding yarn qualities were compared. Findings The results indicate that pressure and deformation of FMTR have little effects on yarn tenacity and hairiness, while have great effects on yarn evenness. For 5.8tex and 4.9tex cotton yarn, yarns spun by FMTR made from sleeved carbon fiber have larger pressure and deformation at the middle of nipper bites of FMR and FMTR, and yarn evenness is better. For 3.9tex cotton yarns, at the middle of nipper bites of FMR and FMTR, FMTR made from steel has smaller pressure. But deformation of FMTR made from steel is larger, and yarn evenness is better. Originality/value This paper studied pressure and deformation of FMTR by finite element method (FEM), which serve as a theoretical underpinning for yarn spinning in three draft zones ring spinning machine.

Applications of Neural Networks in the Hairiness of Ring Spinning Polyester/Cotton Yarn Prediction

2012 ◽  
Vol 549 ◽  
pp. 1055-1059
Author(s):  
Bo Zhao
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Processing Parameters ◽  
Cotton Yarn ◽  
Ring Spinning ◽  
Artificial Neural ◽  
Yarn Hairiness ◽  
Bp Neural Network Model

In this paper, back-propagation (BP) neural network model is introduced and established. This work describes the application of the BP artificial neural network model for the purpose of predicting the polyester/cotton yarn hairiness. This approach has been developed and evaluated with the use of multiple sets of data, comprising of a range of processing parameters. The yarn hairiness of ring spinning is strongly related to the processing parameters. However, it is difficult to establish physical models on the relationship between the processing parameters and the yarn hairiness. Due to the artificial neural network can fully approximate any complex nonlinear system and study dynamic behavior of any serious undetermined system. It has a highly parallel calculation ability, strong robustness and fault tolerance. So using the artificial neural network to predict the polyester/cotton yarn hairiness of ring spinning is a very effective way. The experimental results and corresponding analysis show that the BP neural network model is an efficient technique for the yarn hairiness of ring spinning prediction and has wide prospect in the application of ring spinning yarn production system.

scholarly journals A study on detection of roving tension and fine control of yarn breakage

2021 ◽  
Vol 72 (03) ◽  
pp. 250-255
Author(s):  
CUI PENG ◽  
XUE YUAN
Keyword(s):  
Production Efficiency ◽  
Acquisition System ◽  
Signal Acquisition ◽  
Ring Spinning ◽  
High Quality ◽  
Factors Affecting ◽  
Yarn Quality ◽  
Breakage Rate ◽  
Fine Control ◽  
Rational Production

The fine control of yarn breakage is essential for the production of better yarn quality by reducing the tension fluctuationof roving. The detection of roving tension provides important information regarding the yarn formation during spinning.In the present work, we developed a device for roving-tension detection and regulation, which greatly reduces the yarnbreakage rate and improves the production efficiency of ring spinning. By analysing the factors affecting the rovingtensions, we used a signal acquisition system in conjunction with the tension detection device to regulate the spindlerotate speed to realize the fine control of yarn breakage. Our results indicate that the proposed method can ensure auniform spinning tension of the yarn in ring spinning, which significantly reduces the yarn breakage rate, and boost theyarn production. Our work paves the way toward the rational production of high-quality yarn

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