Prediction of Bursting Strength and Pilling Rating of Three Thread Fleece Fabric using Artificial Neural Network
Year: 2024
Type: article
Abstract: In this work, the bursting strength and pilling rating of polyester-cotton fiber-blended three-thread fleece fabric were predicted using an artificial neural network (ANN) back propagation (BP) model. Bursting strength and pilling were predicted from 50 three-thread fleece fabrics with different stitch lengths, grams per square meter (GSM), yarn counts, and twists per inch. All three-thread fleece fabrics have their own bursting strength and pilling rate, which were used for the prediction. To validate the two models in the training steps, training precision, and simulation precision, 40 fabrics were used for training and 10 fabrics were used for testing, and the predicted pilling property was obtained. The results show that the predicted values of bursting strength and pilling rating were closer to the experimental values, which are determined by the ANN backpropagation (BP) model. This study shows that an optimized model with BP can predict the bursting strength and pilling rating of polyester–cotton three-thread fleece fabrics with acceptable accuracy.
DOI: 10.63261/ijtem115
Authors: Rabiul Islam, Arman Islam, Jobaidur Jisan, Ahmed Muhiminul Haider, Al Muntasir
Institution: Bangladesh University of Textiles
Language: English
Subfield: Polymers and Plastics
Field: Materials Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4408919671