Predicting the pilling propensity of fabrics through artificial neural network modeling

Fabric pilling is affected by many interacting factors. This study uses artificial neural networks to model the multi-linear relationships between fiber, yarn and fabric properties and their effect on the pilling propensity of pure wool knitted fabrics. This tool shall enable the user to gauge the e...

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Bibliographic Details
Published in:Textile research journal 2005-07, Vol.75 (7), p.557-561
Main Authors: Beltran, R, Wang, L, Wang, X
Format: Article
Language:English
Subjects:
Artificial neural networks
Computer based modeling
fabric pilling
Fabrics
Fibers
Mathematical models
Neural networks
Physical properties
simulation models
Specifications
Studies
Wear
Wool
Wool fabrics
woolen fabric
Yarns
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Summary:Fabric pilling is affected by many interacting factors. This study uses artificial neural networks to model the multi-linear relationships between fiber, yarn and fabric properties and their effect on the pilling propensity of pure wool knitted fabrics. This tool shall enable the user to gauge the expected pilling performance of a fabric from a number of given inputs. It will also provide a means of improving current products by offering alternative material specification and/or selection. In addition to having the capability to predict pilling performance, the model will allow for clarification of major fiber, yarn and fabric attributes affecting fabric pilling.
ISSN:0040-5175
1746-7748
DOI:10.1177/0040517505056872