New approaches to establishing translation equations for the total hand value of fabric

The aim of this study is to take new approaches using a one-step transformation process to establish translation equations for total hand evaluations of fabrics by employing a stepwise regression method and an artificial neural network. The key mechanical properties selected from sixteen fabric mechanical properties based on a KES system, using the stepwise regression selection method, are the parameters. The, translation equations are developed directly with parameters without a primary hand value transformation process. In this study, 114 polyester/cotton blended woven fabrics are selected for investigation. From the results, four mechanical properties LC, 2HG, B, and WT are the parameters for developing the translation equations. The correlation coefficients of the translation equations developed from the stepwise regression and artificial neural network methods are 0.925 and 0.955, respectively. Both translation equations have high correlation coefficients between the calculated and practical values. The approaches are identified effectively to develop translation equations for new fabrics in the textile industry.