Abstract
This research paper offers a thorough examination of the use of Artificial-Intelligence & Machine-Learning in sustainable supply chain management . This paper evaluates the existing usage, advantages, problems, and future prospects of AI & ML within the supply chain operations by analyzing the available literature. The findings emphasize the potential of Artificial-Intelligence & Machine-Learning technology to improve decision-making processes, optimize resource allocation, increase supply chain visibility, and promote sustainable practices. The report underlines that, while AI & ML provide tremendous benefits, some difficulties must be solved before they can be successfully implemented. These include assuring data quality, selecting suitable algorithms, dealing with interpretability issues, and dealing with ethical problems.
Cite
CITATION STYLE
Elkady, G., & Hesham Sedky, A. (2023). Artificial Intelligence And Machine Learning For Supply Chain Resilience. Current Integrative Engineering, 1(1), 23–28. https://doi.org/10.59762/cie570390541120231031122614
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