Application of Artificial Neural Networks in yarn manufacturing industry: A critical review
Source abstract
Abstract
Researchers are working hard to handle the intricate interplay and interconnected relationships between fiber properties, process parameters, and consumer requirements in yarn manufacturing. These relationships make a complex network and researchers tried to develop prediction models through artificial neural network (ANN). This paper provides a systematic and comprehensive up to date (2024) overview on applications of ANN in the textile yarn manufacturing (fiber to yarn) sector. In addition, diverse methodologies, approaches, and specific applications of ANN in fiber to yarn are criticized in this study. The limitations, challenges, and future scopes of this subject have been explored by synthesizing the selected relevant publications in the field of textile yarn manufacture and ANNs. The study contributes to the theoretical and practical implications through this review and concludes with a valuable future opportunity. Notwithstanding the fact that the research shows a clear improvement in the implementation of ANN in the yarn manufacturing sector, substantial work remains to be done in these areas.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Textile materials and evaluations · Industrial Vision Systems and Defect Detection · Color perception and design
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Textile Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh
Department of Yarn Engineering, Bangladesh University of Textiles, Dhaka, Bangladesh
Research Centre for Nano-Materials and Energy Technology, Sunway University, Selangor Darul Ehsan, Malaysia
Department of Fabric Engineering, Bangladesh University of Textiles, Dhaka, Bangladesh
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