RELATIVE IMPORTANCE OF FIBER PROPERTIES AFFECTING YARN HAIRINESS IN SOME EGYPTIAN COTTON VARIETIES

Fiber length is one of the major fiber properties that influence yarn strength, evenness, product handle, product luster, and yarn hairiness. To assure yarn quality, fiber passes through a number of machinery during the spinning process, where it is subjected to various sorts of action that modifies the fiber length. As different process parameters are chosen based on fiber length, fiber length analysis throughout the spinning process will benefit in the adjustment of machine parameters to produce better quality yarn. This study will reveal the chronological change in average fiber length at different stages of the carded ring spinning process, as well as a correlation analysis of length change among different phases, using correlation and regression methods. For five distinct mixing samples, raw cotton, card mat, carded sliver, breaker drawn sliver, finisher drawn sliver, roving, and yarn (pneumafil) were examined at each stage from raw cotton to ring frame. Then, using USTER AFIS PRO, all of the samples were numerically evaluated and statistically analyzed using Microsoft Excel 2016. A positive correlation between fiber length changes at several phases was observed in the experiment, with average fiber length increasing in carding, breaker drawing, finisher drawing, and simplex but decreasing in card mat and ring.

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Influence of Egyptian Cotton Fiber Properties and Mechanical Processing on Nep Formation.(Dept.T)

MEJ. Mansoura Engineering Journal ◽

10.21608/bfemu.2021.170994 ◽

2021 ◽

Vol 15 (1) ◽

pp. 12-23

Author(s):

Rizk El-Bealy

Keyword(s):

Cotton Fiber ◽

Mechanical Processing ◽

Fiber Properties ◽

Egyptian Cotton

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Predicting Hairiness for Ring and Rotor Spun Yarns and Analyzing the Impact of Fiber Properties

Textile Research Journal ◽

10.1177/004051759706700909 ◽

1997 ◽

Vol 67 (9) ◽

pp. 694-698 ◽

Cited By ~ 41

Author(s):

Reiyao Zhu ◽

M. Dean Ethridge

Keyword(s):

Back Propagation ◽

Back Propagation Neural Network ◽

Fiber Properties ◽

Fiber Property ◽

Spun Yarns ◽

Neural Network Algorithm ◽

Yarn Hairiness ◽

Rotor Yarn ◽

Optimum Model ◽

The Impact

Models for predicting ring or rotor yarn hairiness are built using a back-propagation neural network algorithm. These models are based on fiber property input measured by three different systems, hvi, afis, and fmt. We compare the prediction results from the different models, which reveal that yarn hairiness measurements from hvi data are superior to other models. The optimum model is based on the availability of all three measurement systems. We also study the impact of each fiber property on yarn hairiness. The dominant effect is fiber length. Each of the remaining properties has a different degree of impact on ring or rotor yarn hairiness.

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The Relative Importance of Fiber Friction and Torsional and Bending Rigidities in Cotton Sliver, Roving, and Yarn

Textile Research Journal ◽

10.1177/004051759206200402 ◽

1992 ◽

Vol 62 (4) ◽

pp. 192-196 ◽

Cited By ~ 4

Author(s):

L. B. DeLuca ◽

D. P. Thibodeaux

Keyword(s):

Cotton Fiber ◽

Relative Importance ◽

Fiber Properties ◽

Cohesive Forces ◽

Temperature And Humidity ◽

Fiber Interaction ◽

Cotton Sliver ◽

Fiber Breaking

In each stage of cotton processing from carding through yarn, the importance of cotton fiber properties and the interaction of fiber on fiber are complex and not fully understood. This work compares how select fiber and fiber interaction properties of raw stock cotton are altered as temperature and humidity are changed independently. Such comparisons provide the key for determining how fiber-to-fiber friction, fiber rigidities, and fiber breaking tenacity and elongation enter into the cohesive forces of cotton sliver, roving, and yarn.

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