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Erschienen in: The International Journal of Advanced Manufacturing Technology 1-2/2021

18.06.2021 | Critical Review

Modeling of textile manufacturing processes using intelligent techniques: a review

verfasst von: Zhenglei He, Jie Xu, Kim Phuc Tran, Sébastien Thomassey, Xianyi Zeng, Changhai Yi

Erschienen in: The International Journal of Advanced Manufacturing Technology | Ausgabe 1-2/2021

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Abstract

As the need for quickly exploring a textile manufacturing process is increasingly costly along with the complexity in the process. The development of manufacturing process modeling has attracted growing attention from the textile industry. More and more researchers shift their attention from classic methods to the intelligent techniques for process modeling as the traditional ones can hardly depict the intricate relationships of numerous process factors and performances. In this study, the literature investigating the process modeling of textile manufacturing is systematically reviewed. The structure of this paper is in line with the procedure of textile processes from yarn to fabrics, and then to garments. The analysis and discussion of the previous studies are conducted on different applications in different processes. The factors and performance properties considered in process modeling are collected in comparison. In terms of inputs’ relative importance, feature selection, modeling techniques, data distribution, and performance estimations, the considerations of the previous studies are analyzed and summarized. It is also concluded the limitations, challenges, and future perspectives in this issue on the basis of the summaries of more than 130 related articles from the point of views of textile engineering and artificial intelligence.

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Metadaten
Titel
Modeling of textile manufacturing processes using intelligent techniques: a review
verfasst von
Zhenglei He
Jie Xu
Kim Phuc Tran
Sébastien Thomassey
Xianyi Zeng
Changhai Yi
Publikationsdatum
18.06.2021
Verlag
Springer London
Erschienen in
The International Journal of Advanced Manufacturing Technology / Ausgabe 1-2/2021
Print ISSN: 0268-3768
Elektronische ISSN: 1433-3015
DOI
https://doi.org/10.1007/s00170-021-07444-1

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