NDLI: Prediction of Yarn Strength Utilization in Cotton Woven Fabrics using Artificial Neural Network

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Journal of The Institution of Engineers (India): Series E : Volume 98

Journal of The Institution of Engineers (India): Series E : Volume 97

Journal of The Institution of Engineers (India): Series E : Volume 96

Journal of The Institution of Engineers (India): Series E : Volume 96, Issue 2, October 2015

Foreword

Modeling and Optimization in Fibrous Materials

A Review on Mathematical Modeling for Textile Processes

An Insight to the Modeling of 1 × 1 Rib Loop Formation Process on Circular Weft Knitting Machine using Computer

Development of Warp Yarn Tension During Shedding: A Theoretical Approach

Experimental Investigations of Woven Textile Tape as Strain Sensor

Optimizing Aqua Splicer Parameters for Lycra−Cotton Core Spun Yarn Using Taguchi Method

Simulation of Stress–Strain Curves of Polyester and Viscose Filaments

Micromagnetic Simulation of Fibers and Coatings on Textiles

Prediction of Yarn Strength Utilization in Cotton Woven Fabrics using Artificial Neural Network

Production of Engineered Fabrics Using Artificial Neural Network–Genetic Algorithm Hybrid Model

Comparative Analysis of Soft Computing Models in Prediction of Bending Rigidity of Cotton Woven Fabrics

Modeling of Abrasion Resistance Performance of Persian Handmade Wool Carpets Using Artificial Neural Network

Journal of The Institution of Engineers (India): Series E : Volume 96, Issue 1, April 2015

Journal of The Institution of Engineers (India): Series E : Volume 95

Journal of The Institution of Engineers (India): Series E : Volume 94

Journal of The Institution of Engineers (India): Series E : Volume 93

Prediction of Yarn Strength Utilization in Cotton Woven Fabrics using Artificial Neural Network

Content Provider	SpringerLink
Author	Mishra, Swapna
Copyright Year	2014
Abstract	The paper presents an endeavor to predict the percentage yarn strength utilization (% SU) in cotton woven fabrics using artificial neural network approach. Fabrics in plain, 2/2 twill, 3/1 twill and 4-end broken twill weaves having three pick densities and three weft counts in each weave have been considered. Different artificial neural network models, with different set of input parameters, have been explored. It has been found that % SU can be predicted fairly accurately by only five fabric parameters, namely the number of load bearing and transverse yarns per unit length, the yarn crimp % in the load bearing and transverse directions and the float length of the weave. Trend analysis of the artificial neural network model has also been carried out to see how the various parameters affect the % SU. The results indicate that while an increase in the number of load bearing or transverse yarns increases the % SU, an increase in the float length and the crimp % in the yarns have a detrimental effect.
Starting Page	151
Ending Page	157
Page Count	7
File Format	PDF
ISSN	22502483
Journal	Journal of The Institution of Engineers (India): Series E
Volume Number	96
Issue Number	2
e-ISSN	22502491
Language	English
Publisher	Springer India
Publisher Date	2014-12-04
Publisher Place	New Delhi
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Engineering Artificial neural networks Percentage yarn strength utilization Tensile strength Woven fabrics Structure–property relationship
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Chemical Engineering Materials Science

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
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Prediction of Yarn Strength Utilization in Cotton Woven Fabrics using Artificial Neural Network

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