Vol. 4 No. 2 (2024): African Journal of Artificial Intelligence and Sustainable Development
Articles

The Role of AI-Based Decision Support Systems in Optimizing U.S. Manufacturing and Logistics Operations

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  • Prof. Rajesh Mehta
Prof. Rajesh Mehta
Senior Researcher, Microsoft Research, Bangalore, India

Published 01-09-2024

Keywords

  • Decision Support Systems,
  • Manufacturing,
  • Logistics
Creative Commons License

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

How to Cite

[1]
Prof. Rajesh Mehta, “The Role of AI-Based Decision Support Systems in Optimizing U.S. Manufacturing and Logistics Operations”, African J. of Artificial Int. and Sust. Dev., vol. 4, no. 2, pp. 252–266, Sep. 2024, Accessed: Nov. 21, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/163

Abstract

The introduction sets the stage for the essay by providing an overview of the topic and its relevance to U.S. manufacturing and logistics. It serves as an entry point to the discussion of AI-based decision support systems and their impact on the industry. AI-based decision support systems have become increasingly vital in optimizing manufacturing and logistics operations in the U.S. These systems not only enhance operational efficiency but also contribute to long-term economic viability, social cohesiveness, inclusion, and environmental sustainability [1].

Furthermore, the integration of intelligent systems in manufacturing has shown promising developments and future prospects. Specialized surveys have highlighted the application of fuzzy set theory, genetic algorithms, expert systems, and neural networks in various aspects of manufacturing, including production management, quality control, process planning, and flexible manufacturing systems control [2]. These advancements underscore the potential of AI-based decision support systems to revolutionize U.S. manufacturing and logistics operations.

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