Predicting Fabric Drapability Property by Using an Artificial Neural Network. Issue 3 (September 2018)

• Record Type: Journal Article
• Authors: Taieb, Amine Hadj; Mshali, Slah; Sakli, Faouzi
• Is Part Of: Journal of engineered fibers and fabrics. Volume 13:Issue 3(2018)
• Publication Date: 2018-09
• Subjects: Back-propagation -- correlation coefficient -- fabric drape -- neural network; Nonwoven fabrics -- Periodicals; Fibers -- Periodicals; Fibers; Nonwoven fabrics; Periodicals; 677.6
• DOI: 10.1177/155892501801300312
• Languages: English
• ISSNs: 1558-9250

Abstract

Drape, one of the most important properties of fabric, has played significant role in providing graceful aesthetic effects in garments. Drapability of textiles is judged subjectively and is dependent on people's skill and experience, which render difficulties during drape comparisons, especially when judged by different people. This work reports the results of a study on predicting the drapability of woven fabric using an artificial neural network. It was established that drapability could be predicted from the mechanical properties of fabric at low-stress.