PREDICTION OF DIMENSIONAL CHANGE IN FINISHED FABRIC THROUGH ARTIFICIAL NEURAL NETWORKS

Year 2018, Volume: 28 Issue: 1, 43 - 51, 31.03.2018

Mihriban Kalkancı Mahmut Sinecen Gülseren Kurumer

Abstract

When
anti-shrinkage precaution is taken for finishing processes, shrinkage could be
observed with cotton and viscose fabrics by 8-15% and 20%, respectively.
Therefore, capability of estimation of shrinkage rate for fabrics at the end of
finishing would be a significant advantage. This study tried to estimate
the shrinkage of single jersey and interlock fabrics at the end of relaxation
processes by means of the Artificial Neural Networks (ANN). To that
end totally 72 varieties of fabric were manufactured in two groups of the
elastane and the non-elastane fabrics. Then, in each of two groups included 36
different varieties on the basis of single jersey and interlock weaving types
using six different raw materials in three different densities.The processes were applied to fabrics
during finishing process are thermo-fixing, washing, drying and sanforizing
process.ANN model was used to predict dimensional change at the end of the
sanforizing. For ANN, the two-layer feed-forward perceptron, also called single
hidden layer feed-forward neural network was used to estimate dimensional
change of width and length. Finally, the ANN exhibited successful
performance in prediction of dimensional change in fabrics. The prediction of
the dimensional properties produced by the neural network model was proved to
be highly reliable (R²> 0.98).

Keywords

Dimensional change, ANN, estimation, finished fabric, finishing

PREDICTION OF DIMENSIONAL CHANGE IN FINISHED FABRIC THROUGH ARTIFICIAL NEURAL NETWORKS

Abstract

When anti-shrinkage precaution is taken for finishing processes, shrinkage could be observed with cotton and viscose fabrics by 8-15% and 20%, respectively. Therefore, capability of estimation of shrinkage rate for fabrics at the end of finishing would be a significant advantage. This study tried to estimate the shrinkage of single jersey and interlock fabrics at the end of relaxation processes by means of the Artificial Neural Networks (ANN). To that end totally 72 varieties of fabric were manufactured in two groups of the elastane and the non-elastane fabrics. Then, in each of two groups included 36 different varieties on the basis of single jersey and interlock weaving types using six different raw materials in three different densities.The processes were applied to fabrics during finishing process are thermo-fixing, washing, drying and sanforizing process.ANN model was used to predict dimensional change at the end of the sanforizing. For ANN, the two-layer feed-forward perceptron, also called single hidden layer feed-forward neural network was used to estimate dimensional change of width and length. Finally, the ANN exhibited successful performance in prediction of dimensional change in fabrics. The prediction of the dimensional properties produced by the neural network model was proved to be highly reliable (R²> 0.98).

Keywords

Dimensional change, ANN, estimation, finished fabric, finishing

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