Artificial Neural Network System for Prediction of Dimensional Properties of Cloth in Garment Manufacturing: Case Study on a T-Shirt

Abstract

The purpose of the present study was to estimate dimensional measure properties of T-shirts made up of Single Jersey and interlock fabrics through Artificial Neural Networks (ANN). To that end, 72 different types of t-shirts were manufactured under 2 different fabric groups, each was consisting of 2 groups: one with elastane and the other without. Each of these groups were manufactured from six different materials in three different densities through two different knitting techniques of single jersey and interlock. For estimation of dimensional changes in these T-shirts, models including feed-forward, back-propagated, the momentum learning rule and sigmoid transfer function were utilized. As a result of the present study, the ANN system was found to be successful in estimation of pattern measures of garments. The prediction of dimensional properties produced by the neural network model proved to be highly reliable (R2> 0.99).

Artificial neural network and multiple linear regression modeling for predicting thermal transmittance of plain-woven cotton fabric

“…These applications include the classification of errors in textile operations, estimates of yarn quality parameters, classification of knitted and woven fabrics, estimation of fabric perception features, prediction of clothing comfort, determination of air permeability in knitted and woven fabrics, as well as estimation of fabric drape and mechanical properties such as static tear strength. 38,39…”

“…These applications include the classification of errors in textile operations, estimates of yarn quality parameters, classification of knitted and woven fabrics, estimation of fabric perception features, prediction of clothing comfort, determination of air permeability in knitted and woven fabrics, as well as estimation of fabric drape and mechanical properties such as static tear strength. 38,39 MLR model MLR is a widely employed statistical technique in research, especially in the fields of quantitative structure-activity relationship models (QSAR). This strategy works well because of its straightforwardness and simplicity of understanding.…”

Artificial Neural Network-based Prediction Technique for Waterproofness of Seams Obtained by Using Fusible Threads

“…ANN is a method used in forecasting in many subjects in textiles. It has been used in the estimation of body dimensions, fabric permeability, body types, thermal resistance of fabrics, needle temperature depending on machine speed, fabric elongation, convective and radiant heat transfer indexes of fabrics and many other issues until today [8][9][10][11][12][13][14]. In these studies, it was concluded that the ANN predicted expected outputs were sufficiently successful.…”

Prediction of garment fit level in 3D virtual environment based on artificial neural networks

“…Currently, AI-based ML techniques, such as artificial neural networks (ANN), fuzzy logic, and genetic algorithms, have been intensively applied in the fashion industry [17][18][19] in fashion product design, [8][9]20 garment and fabric product evaluation, [21][22][23][24][25] fashion forecasting, 26 garment comfort estimation, 27,28 apparel manufacturing, [29][30][31] fashion retailing, [32][33][34] and garment supply chain management. 35,36 However, little attention has been paid to predicting garment fit level based on the virtual try-on using an ANN technique.…”