Vol. 4 No. 2 (2024): Journal of AI-Assisted Scientific Discovery
Articles

The Role of AI-Driven Predictive Maintenance in Enhancing U.S. Manufacturing Operations

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  • Dr. Yu Han
Dr. Yu Han
Associate Professor of Computer Science, Shanghai Jiao Tong University, China
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Published 30-09-2024

Keywords

  • Predictive Maintenance,
  • Manufacturing Operations
Creative Commons License

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

How to Cite

[1]
Dr. Yu Han, “The Role of AI-Driven Predictive Maintenance in Enhancing U.S. Manufacturing Operations”, Journal of AI-Assisted Scientific Discovery, vol. 4, no. 2, pp. 246–266, Sep. 2024, Accessed: Nov. 21, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/160

Abstract

Manufacturing is at the core of the U.S. economy. The long-term vitality of the manufacturing sector has a direct relationship with the vitality of the overall national economy. Rapid revitalization and improvement in the global competitiveness of the U.S. manufacturing sector are essential for sustainable economic recovery and growth. In recent years, the manufacturing industry has undergone dramatic changes due to rising competitive pressure, deregulation and offshoring, and advancing technology. The increasing capability of machine learning, artificial intelligence (AI), and automation technologies combined with the greater availability of machine data have created opportunities for smart and data-driven manufacturing systems.

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