Vol. 3 No. 2 (2023): African Journal of Artificial Intelligence and Sustainable Development
Articles

AI-Driven Solutions for Enhancing Sustainability in U.S. Manufacturing Supply Chains

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  • Dr. David Kim
Dr. David Kim
Associate Professor of Cybersecurity, Kookmin University, South Korea
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Published 20-12-2023

Keywords

  • Sustainability,
  • U.S. Manufacturing,
  • Supply Chains
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
D. D. Kim, “AI-Driven Solutions for Enhancing Sustainability in U.S. Manufacturing Supply Chains”, African J. of Artificial Int. and Sust. Dev., vol. 3, no. 2, pp. 362–369, Dec. 2023, Accessed: Dec. 23, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/193

Abstract

AI has emerged as a promising tool for addressing sustainability challenges in manufacturing supply chains. The integration of AI technologies, such as machine learning and data analytics, holds the potential to optimize various components of the supply chain, including planning, sourcing, manufacturing, warehousing, distribution, and customer interface. [1] emphasizes that AI algorithms excel in leveraging large datasets from diverse sources, enabling machines to derive unique insights and perform tasks more efficiently than humans. This aligns with the scalability of AI within modern supply chains, which generate substantial volumes of data and operate within a network-based architecture. Furthermore, [2] highlight that the costs associated with AI applications in manufacturing should be viewed as long-term investments that promote environmental sustainability.

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References

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