Predicting the seam efficiency of sewn blended fabrics using ANN and linear regression models

Abstract

In most cases, quality of sewn apparel products is characterized by seam performance. The durability of the seam is mainly defined by its efficiency along the seam line; therefore it is one of the most important characteristics to obtain the desired seam quality. Throughout this study, seam efficiencies of woven blended fabrics were predicted using two different methodologies, i.e. ANN and regression methods. ANN with four neurons input layer, 15 neuron hidden layer and output layer with one neuron focusing on the seam efficiency was used and compared to regression line. The input variables in both predictive modes were polyester ratios, sewing needle size, stitch density and sewing thread count. The findings of this work revealed that ANN predictive model is outperformed the multiple linear regression one with lower vales of RMSE and MBE and high R2 values.