Namangan Institute of Engineering and Technology
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10.25.2023
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Another challenge is the complexity of textile materials. Textile materials are made up of a
variety of different fibers and can be woven or knitted into complex structures. This makes it difficult
to develop AI algorithms that can accurately assess the quality of all types of textile materials.
Despite the challenges, there are a number of opportunities for the use of AI in textile quality
control. AI technologies can help to improve the efficiency, accuracy, and consistency of quality
testing. This can lead to significant benefits for textile manufacturers, such as reduced costs,
improved product quality, and increased customer satisfaction.
Conclusion. AI technologies are transforming the textile industry, including in the area of
quality control. AI-powered systems can be used to automate and improve the accuracy of quality
testing, leading to significant benefits for textile manufacturers.While there are some challenges in
the use of AI for textile quality control, such as the need for large datasets of training data and the
complexity of textile materials, the opportunities are significant. AI technologies can help textile
manufacturers to improve the quality of their products and reduce costs.
References
[1] A. Haldar, P. K. Das, and S. K. Samanta, "Application of artificial intelligence in textile
industry", Journal of the Textile Association, vol. 80, no. 10, pp. 72-82, 2019.
[2] S. K. Samanta, P. K. Das, and A. Haldar, "Artificial intelligence techniques for textile quality
control", **Journal
