Contribution on Modeling of Bagged Denim Fabric Behavior After Mixed Washing Using PCA and Regression Techniques - Abir Ben Fraj; Boubaker Jaouachi (Journal of Natural Fibers)
This study evaluates the effect of mixed washing treatment on the bagging behavior of denim fabrics. Six types of denim fabrics were washed under different conditions. Then, the bagging test was applied. Furthermore, the most influential factors of this treatment on the bagging ability of denim fabric were discussed using the main effect plots. This method shows that the quantity of pumice stone, the quantity of enzyme and the fabric are the most influencing factors. The increase in the amount of enzyme or pumice stone increases the occurrence of the bagging problem. Since the fabric is the dominant factor for all bagging properties, the characterization with Kawabata instruments of treated and untreated fabrics was performed. Then, we used the principal component analysis method to select the most important parameters. A reduction of 52.78% in parameters was achieved. Finally, the linear regression models were obtained to predict the bagging properties. The regression coefficients (R2) range between 96.85% and 99.43% and the adjusted R2 is between 92.34% and 98.13%, which confirms the efficiency of our models. These models are crucial for the manufacturers of washing denim since they could help the industrials to predict denim fabric’s bagging behavior after mixed washing.