The integration of artificial intelligence and data science in optimizing the global textile supply chain: a strategic and operational analysis
The integration of artificial intelligence and data science in optimizing the global textile supply chain: a strategic and operational analysis
DOI:
https://doi.org/10.51473/rcmos.v1i2.2025.2073Keywords:
Artificial Intelligence. Textile Supply Chain. Data Science. Operational Efficiency. Industry 4.0.Abstract
The fashion and textile industry is facing a historical turning point, driven by the convergence of the need for sustainability, the demand for mass customization, and the disruption of traditional supply chains. This scientific article aims to analyze, from a technical and managerial perspective, how the application of Artificial Intelligence (AI), Machine Learning, and Data Science acts as a catalyst for operational efficiency and competitiveness in manufacturing and retail. The methodology consists of a systematic and integrative bibliographic review, exploring concepts of Industry 4.0, Lean Manufacturing, and predictive demand models. The implementation of inventory optimization algorithms, the automation of productive workflows, and the impact of reshoring on the North American and global economies are discussed. The results indicate that the adoption of advanced technologies is not just a competitive advantage but an imperative for the financial survival and environmental compliance of companies in the sector. It is concluded that Data-Driven Management is the only viable path to mitigate market volatility and ensure sustainable growth.
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Copyright (c) 2025 Adriana Jikal (Autor)
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