scholarly journals Effects of Opening Roller and Navel Types on %100 Polyester Open-End Rotor Yarn Properties

2014 ◽  
Vol 19 (1) ◽  
pp. 1
Author(s):  
Gözde BUHARALI ◽  
Sunay ÖMEROĞLU
Keyword(s):  
Yarn Properties ◽  
Rotor Yarn

scholarly journals Comparison of the Effects of Different Cotton Fibre Wastes on Different Yarn Types

2017 ◽  
Vol 25 (0) ◽  
pp. 19-30 ◽  
Author(s):  
Demet Yilmaz ◽  
Sinem Yelkovan ◽  
Yasir Tirak
Keyword(s):  
Comparative Research ◽  
Raw Material ◽  
Cotton Yarn ◽  
High Quality ◽  
Yarn Properties ◽  
Cotton Fibres ◽  
Yarn Production ◽  
Rotor Yarn ◽  
Different Levels

In order to make a contribution to the reduction of raw material costs, in the present study the effect of reused cotton fibres on the quality of conventional ring and OE-rotor yarns was investigated. In the yarn production, it three different waste fibres were taken from a cotton yarn production line and blended with primary cotton fibres at five different levels varying from 5% to 40%. In literature, studies have concentrated on the usage of recovered waste fibre in OE-rotor yarn production. However, to date there has been limited extensive and comparative research on the effect of recovered fibre quality on different yarn properties to determine the possibility of high-quality yarn production from reused fibres. In the study, we focused on the effect of different waste types as well as the amount of waste in the blends on the properties of different yarn types.

The Spinning Quality Control Management Based on Decision Making by Data Mining Techniques

2018 ◽  
Vol 7 (1) ◽  
pp. 72
Author(s):  
Khalid AA Abakar ◽  
Chongwen Yu
Keyword(s):  
Data Mining ◽  
Kernel Functions ◽  
Support Vector ◽  
Ann Model ◽  
Data Mining Techniques ◽  
Yarn Quality ◽  
Yarn Properties ◽  
Svm Model ◽  
Rbf Kernel

This work demonstrated the possibility of using the data mining techniques such as artificial neural networks (ANN) and support vector machine (SVM) based model to predict the quality of the spinning yarn parameters. Three different kernel functions were used as SVM kernel functions which are Polynomial and Radial Basis Function (RBF) and Pearson VII Function-based Universal Kernel (PUK) and ANN model were used as data mining techniques to predict yarn properties. In this paper, it was found that the SVM model based on Person VII kernel function (PUK) have the same performance in prediction of spinning yarn quality in comparison with SVM based RBF kernel. The comparison with the ANN model showed that the two SVM models give a better prediction performance than an ANN model.

Discriminant analysis-based modeling of cotton fiber and yarn properties

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Baneswar Sarker ◽  
Shankar Chakraborty
Keyword(s):  
Discriminant Analysis ◽  
Physical Properties ◽  
Cotton Fiber ◽  
Fiber Strength ◽  
Natural Fibers ◽  
Content Type ◽  
Fiber Properties ◽  
Yarn Properties ◽  
Fiber Fineness ◽  
Genetic And Environmental Factors

Purpose Like all other natural fibers, the physical properties of cotton also vary owing to changes in the related genetic and environmental factors, which ultimately affect both the mechanics involved in yarn spinning and the quality of the yarn produced. However, information is lacking about the degree of influence that those properties impart on the spinnability of cotton fiber and the strength of the final yarn. This paper aims to discuss this issue. Design/methodology/approach This paper proposes the application of discriminant analysis as a multivariate regression tool to develop the causal relationships between six cotton fiber properties, i.e. fiber strength (FS), fiber fineness (FF), upper half mean length (UHML), uniformity index (UI), reflectance degree and yellowness and spinning consistency index (SCI) and yarn strength (YS) along with the determination of the respective contributive roles of those fiber properties on the considered dependent variables. Findings Based on the developed discriminant function, it can be revealed that FS, UI, FF and reflectance degree are responsible for higher YS. On the other hand, with increasing values of UHML and fiber yellowness, YS would tend to decrease. Similarly, SCI would increase with higher values of FS, UHML, UI and reflectance degree, and its value would decrease with increasing FF and yellowness. Originality/value The discriminant functions can effectively envisage the contributive role of each of the considered cotton fiber properties on SCI and YS. The discriminant analysis can also be adopted as an efficient tool for investigating the effects of various physical properties of other natural fibers on the corresponding yarn characteristics.

scholarly journals Modal–Cotton Fibre Blend Ratio and Ring Frame Parameter Optimisation Through the Taguchi Method

2019 ◽  
Vol 19 (1) ◽  
pp. 86-96
Author(s):  
R Maheswaran ◽  
V Srinivasan
Keyword(s):  
Parametric Design ◽  
Ring Spinning ◽  
Anova Analysis ◽  
Blend Ratio ◽  
Blended Yarn ◽  
System A ◽  
Ring Frame ◽  
Yarn Properties ◽  
Yarn Tenacity ◽  
Setting Parameters

Abstract The influence of Modal–cotton (MC) fibre blend ratio and ring frame machine parameters such as front top roller loading and break draft on the blended yarn properties has been studied. Compact MC blended yarn samples of 14.75 tex with three different MC fibre blend ratio has been produced in a LR 6 ring spinning frame fitted with Suessen Compact drafting system. A robust design optimisation to minimise the variations of the output yarn properties such as blended yarn tenacity, yarn unevenness and hairiness caused because of the variations in the material as well as machine setting parameters is achieved through the Taguchi parametric design approach. It is found that the maximum compact MC blended yarn tenacity is 23.76 g/tex, which is influenced very much by MC fibre blend ratio but meagrely by top roller loading and break draft. Similarly, the minimum 9.54 U% and 3.59 hairiness index are achieved with 100:0 and 70:30 MC fibre blend ratio, respectively, at 23-kg top roller loading. Statistical ANOVA analysis is performed on the results and optimum values are obtained within the 95% confidential level through confirmation experiments.

Improving fiber trapping with a contact surface during the ring twisting of two cotton yarns

2012 ◽  
Vol 82 (3) ◽  
pp. 272-279 ◽  
Author(s):  
Zhigang Xia ◽  
Weilin Xu ◽  
Xungai Wang
Keyword(s):  
Contact Surface ◽  
Plane Surface ◽  
Geometrical Model ◽  
Variation Analysis ◽  
Significance Level ◽  
Yarn Properties ◽  
Cotton Yarns ◽  
Grooved Surface ◽  
Yarn Hairiness ◽  
Plied Yarn

In this study, a geometrical model was introduced to improve the hair trapping via a surface contacting the yarn-twisting triangle during ring twisting of two single yarns. The fiber-trapping improvement with the contact surface was analyzed theoretically. Then, single Ne 80 ring cotton yarns were used to produce two-ply yarns under different ring-twisting conditions, namely conventional twisting, dry twisting of yarns with a plane surface, wet twisting of yarns with a plane surface, dry twisting of yarns with a grooved surface, and wet twisting of yarns with a grooved surface. Plied yarn properties, including yarn hairiness, strength, and irregularity, were tested. The Student Newman Keuls (SNK) test and variation analysis were also carried out in the SPSS program to study the effect of different contact surfaces on related yarn properties; the significance level was 0.05 for the SNK test and variation analysis. The hairiness of plied yarns was significantly reduced when twisting with the plane or grooved surface, especially for the wet twisting cases. This corresponds well with our model on improving fiber trapping.

Fiber Blending Irregularities in Cross Sections and on Yarn Surfaces in Relation to Yarn Properties

1988 ◽  
Vol 58 (5) ◽  
pp. 291-298 ◽  
Author(s):  
Izabella Krucińnska
Keyword(s):  
Surface Analysis ◽  
Cross Sections ◽  
Original Method ◽  
New Method ◽  
Cross Sectional ◽  
Yarn Properties ◽  
Yarn Surface ◽  
Fiber Blending

An analysis of fiber blending irregularities is presented in relation to the disturbances of blend yarn properties resulting from these phenomena. Fiber blending irregularities were assessed using the original method of yarn surface analysis and a new method of yarn cross-sectional division. These methods correctly reflect the disturbances in the mechanical and aesthetic yarn properties resulting from non-uniform mixing of constituent fibers.

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