Prediction of pilling of polyester–cotton blended woven fabric using artificial neural network models

Qi Xiao,Danyang Li,Rui Wang,Hongyu Sun,Limin Wang,Shujie Zhang

doi:10.1177/1558925019900152

Abstract

In this article, an intelligent pilling prediction model using back-propagation neural network model and an optimized model with genetic algorithm is introduced. Genetic algorithm is proposed in consideration of the initial weight and threshold of back-propagation artificial neural network, and further improves training speed and the accuracy for prediction pilling of polyester–cotton blended woven fabrics. The results show that the maximum numbers of training steps of the optimized model by genetic algorithm are reduced from 164 steps to 137 steps compared with that of back-propagation model. The training fitness of optimized model by genetic algorithm is improved from 0.914 to 0.945. The simulation fitness is increased from 0.912 to 0.987. And the root mean square error decreased from 1.0431 to 0.6842. The optimized model by genetic algorithm shows a better agreement between the experimental and predicted values.

Highlights

The pilling of fabrics is a classic problem for the apparel industries, especially for polyester blended fabrics.[1]
Many researchers have investigated the influence of numerous factors contributing to the pilling of fabrics
Yarn twist, twist ratio, warp density, weft density, fabric tightness, and fabric thickness are the most effective factors. These six factors are used as the input variables of the model, and the number of pills on the surface of fabrics after pilling test is taken as the output variable

Summary

Introduction

The pilling of fabrics is a classic problem for the apparel industries, especially for polyester blended fabrics.[1] Polyester–cotton blended woven fabrics which have crisp, wrinkle resistance, dimensional stability and moisture absorption properties have been developed and are more and more popular among people. Polyester–cotton woven fabrics have some disadvantages, such as easy pilling, which affect the appearance and handle of fabrics. It is realized that the problem of pilling is one of the biggest quality issues for polyester–cotton blended fabrics. Many factors have been identified to affect fabric pilling, which include fiber properties (type,[2] modulus,[3] friction coefficient4), yarn properties (spinning method,[5] twist,[6] yarn count7) and fabric properties (structure,[8] cover factor9), whose synergism determines the pilling propensity. Many researchers have investigated the influence of numerous factors contributing to the pilling of fabrics. Beltran et al.[10] found that the larger the fabric

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