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Predicting the pilling propensity of fabrics through artificial neural network modeling
journal contribution
posted on 2005-01-01, 00:00 authored by Rafael Beltran, Lijing Wang, Xungai WangFabric 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.
History
Journal
Textile research journalVolume
75Issue
7Pagination
557 - 561Publisher
SageLocation
Thousand Oaks, Calif.Publisher DOI
ISSN
0040-5175eISSN
1746-7748Language
engNotes
The final, definitive version of this article has been published in the Journal, Textile research journal, Vol 75, Issue Number 7, 2005, © SAGE Publications Ltd, 2005 by SAGE Publications Ltd at the Textile research journal page: http://trj.sagepub.com/ on SAGE Journals Online: http://online.sagepub.com/Publication classification
C1 Refereed article in a scholarly journalCopyright notice
2005, SAGE PublicationsUsage metrics
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