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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This research was supported by the funds from the National Key R&D Program of China (Project No: 2019YFB1706300), and Scientific Research Project of Hubei Provincial Department of Education, China (Project No: Q20191707). The first author would like to express his gratitude to China Scholarship Council for supporting this study (CSC, Project No. 201708420166).
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He, Z., Xu, J., Tran, K.P. et al. Modeling of textile manufacturing processes using intelligent techniques: a review. Int J Adv Manuf Technol 116, 39–67 (2021). https://doi.org/10.1007/s00170-021-07444-1
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