scholarly journals Factors affecting properties of yarn produced by friction spinning machine. Part 1: Effect of suction pipe bigure and sige on spun yarn properties.

1990 ◽  
Vol 43 (6) ◽  
pp. T45-T52 ◽  
Author(s):  
Mamoru Shimakura ◽  
Hisaaki Kato
Keyword(s):  
Machine Part ◽  
Factors Affecting ◽  
Suction Pipe ◽  
Spun Yarn ◽  
Yarn Properties

scholarly journals Open-End Yarn Properties Prediction Using HVI Fibre Properties and Process Parameters

2017 ◽  
Vol 17 (1) ◽  
pp. 6-11 ◽  
Author(s):  
Hanen Ghanmi ◽  
Adel Ghith ◽  
Tarek Benameur
Keyword(s):  
Response Surface ◽  
Process Parameters ◽  
Processing Parameters ◽  
Raw Material ◽  
Spun Yarn ◽  
Yarn Properties ◽  
Spun Yarns ◽  
Yarn Count ◽  
Input Variables ◽  
Rotor Spun Yarn

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.

Analysis of the Additional Twists on the Fiber Band in Compact Field of Compact Spinning

2011 ◽  
Vol 175-176 ◽  
pp. 380-384
Author(s):  
Jun Wang ◽  
Han Guang Liu ◽  
Jian Ping Yang ◽  
Guang Wei Chen ◽  
Ting Fu
Keyword(s):  
Mathematic Model ◽  
Factors Affecting ◽  
Tilting Angle ◽  
Compact Field ◽  
Spun Yarn ◽  
Compact Spinning ◽  
Spinning Speed ◽  
Suction Slot

Based on the analysis of the motion of fiber band in compact field, a mathematic model is proposed in this article. The factors affecting the additional twists and final twists of the compact spun yarn, such as diameter of the fiber band in the compact field, tilting angle of suction slot in profile tube and spinning speed, were discussed in detail. The validity of the model was validated by experiments.

Comparative study of viscose yarn properties spun with a softening device and pressure plate

2019 ◽  
Vol 89 (23-24) ◽  
pp. 4992-5005
Author(s):  
Keshuai Liu ◽  
Duo Xu ◽  
Jiang Wei ◽  
Junlong Ni ◽  
Shengming Yang ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Control Method ◽  
Breaking Strength ◽  
Main Body ◽  
Pressure Plate ◽  
Collaborative Control ◽  
Spun Yarn ◽  
Yarn Properties ◽  
Reduce Energy Consumption ◽  
Save Energy

In order to reduce energy consumption and further improve the performance of viscose yarns, this study introduced a collaborative control method to improve spun yarn performance by contacting the spinning strand with both a softening device and a pressure plate. In this study, we analyze the improving mechanism of spun yarn performance using the softening device and pressure plate. The results show that thermal insulation layer formed between the softening device and pressure plate could heat the yarns in all directions to further re-wrap out-exposed hairiness into the main body of yarns and save energy consumption. Four groups of 19.7 tex viscose yarns were spun with different collaborative apparatus (with and without the softening device or pressure plate). Four groups of viscose yarns were tested in terms of hairiness, unevenness, and tensile property. Moreover, the experimental results show that collaborative apparatus with the softening device and pressure plate could significantly improve yarn performance, including CV value, hairiness, break elongation, and breaking strength to 11.3%, 18.94, 12.9%, and 311.0 cN, respectively.

scholarly journals An Intelligent Model to Predict Breaking Strength of Rotor Spun Yarns Using Gene Expression Programming

2012 ◽  
Vol 7 (2) ◽  
pp. 155892501200700 ◽  
Author(s):  
Abdolrasool Moghassem ◽  
Alireza Fallahpour ◽  
Mohsen Shanbeh
Keyword(s):  
Gene Expression ◽  
Breaking Strength ◽  
Gene Expression Programming ◽  
Ann Model ◽  
Spun Yarn ◽  
Yarn Properties ◽  
Spun Yarns ◽  
Artificial Neural Network Ann ◽  
High Degree ◽  
Prediction Approach

Exploring relationships between characteristics of a yarn and influencing factors is momentous subject to optimize the selection of the variables. Different modelling methodologies have been used to predict spun yarn properties. Developing a prediction approach with higher degree of precision is a subject that has received attention by the researchers. In the last decade, Artificial Neural Network (ANN) has been developed successfully for textile nonlinear processes. In spite of the precision, ANN is a black box and does not indicate inter-relationship between input and output parameters. Hence, Gene Expression Programming (GEP) is presented here as an intelligent algorithm to predict breaking strength of rotor spun yarns based on draw frame parameters as one of the most important stages in spinning line. Forty eight samples were produced and different models were evaluated. Prediction performance of the GEP was compared with that of ANN using Mean Square Error (MSE) and correlation coefficient (R2-Value) parameters on test data. The results showed a better capability of the GEP model in comparison to the ANN model. The R2-value and MSE were 97% and 0.071 respectively which means desirable predictive power of GEP algorithm. Finally, an equation was extracted to predict breaking strength of the yarns with a high degree of accuracy using GEP algorithm.

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