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Predicting worsted spinning performance with an artificial neural network model

Beltran, Rafael, Wang, Lijing and Wang, Xungai 2004, Predicting worsted spinning performance with an artificial neural network model, Textile research journal, vol. 74, no. 9, pp. 757-763.

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Title Predicting worsted spinning performance with an artificial neural network model
Author(s) Beltran, Rafael
Wang, Lijing
Wang, Xungai
Journal name Textile research journal
Volume number 74
Issue number 9
Start page 757
End page 763
Publisher Sage
Place of publication Thousand Oaks, Calif.
Publication date 2004
ISSN 0040-5175
1746-7748
Summary For a given fiber spun to pre-determined yarn specifications, the spinning performance of the yarn usually varies from mill to mill. For this reason, it is necessary to develop an empirical model that can encompass all known processing variables that exist in different spinning mills, and then generalize this information and be able to accurately predict yarn quality for an individual mill. This paper reports a method for predicting worsted spinning performance with an artificial neural network (ANN) trained with backpropagation. The applicability of artificial neural networks for predicting spinning performance is first evaluated against a well established prediction and benchmarking tool (Sirolan YarnspecTM). The ANN is then subsequently trained with commercial mill data to assess the feasibility of the method as a mill-specific performance prediction tool. Incorporating mill-specific data results in an improved fit to the commercial mill data set, suggesting that the proposed method has the ability to predict the spinning performance of a specific mill accurately.
Notes The final, definitive version of this article has been published in the Journal, Textile research journal, Vol 74, Issue Number 9, 2004, © SAGE Publications Ltd, 2004 by SAGE Publications Ltd at the Textile research journal page: http://trj.sagepub.com/ on SAGE Journals Online: http://online.sagepub.com/
Language eng
Field of Research 091012 Textile Technology
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2004, SAGE Publications
Persistent URL http://hdl.handle.net/10536/DRO/DU:30002564

Document type: Journal Article
Collections: School of Engineering and Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.