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

Leveraging AI for Process Optimization in Tech Product Manufacturing: Case Studies in Mobile, Laptops, and Semiconductor Industries

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  • Dr. Daniel Koppelman
Dr. Daniel Koppelman
Professor of Computer Science, University of Haifa, Israel
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Published 03-10-2024

Keywords

  • Process Optimization,
  • Tech Product Manufacturing,
  • Semiconductor Industries
Creative Commons License

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

How to Cite

[1]
Dr. Daniel Koppelman, “Leveraging AI for Process Optimization in Tech Product Manufacturing: Case Studies in Mobile, Laptops, and Semiconductor Industries”, Journal of AI-Assisted Scientific Discovery, vol. 4, no. 2, pp. 136–157, Oct. 2024, Accessed: Nov. 12, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/154

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) have become integral in the manufacturing industry, particularly in optimizing processes within the tech product manufacturing sector. [1] emphasize the significance of AI technologies such as ML, knowledge graphs, and human-computer interaction in improving system performance metrics within manufacturing. They highlight the role of intelligent manufacturing systems, which encompass smart manufacturing devices and intelligent manufacturing services, and the utilization of ML algorithms at the device layer to meet real-time requirements. Moreover, AI is employed in wireless channel prediction, mobile network handoff optimization, and network congestion control, demonstrating the diverse applications of AI in manufacturing.

Furthermore, [2] underscore the development of centralized and automated real-time monitoring systems using machine learning-based techniques to reduce labor costs and enhance energy efficiency in smart manufacturing. They discuss the deployment of intelligent data analysis, real-time supervision, and IoT techniques, as well as the application of deep learning-based object detection and text recognition methods in industrial production supervision. These references collectively illustrate the broad spectrum of AI applications in manufacturing, setting the stage for understanding the subsequent case studies in mobile, laptop, and semiconductor industries.

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