AI-Based Optimization of Manufacturing Processes to Bring Tech Product Production Back to the USA

Strategies and Outcomes

Authors

  • Dr. Ayşe Gülcü Professor of Electrical and Electronics Engineering, Istanbul University, Turkey Author

Keywords:

Manufacturing Processes, Tech Product

Abstract

Access to high-quality products has never been more important than it is today. In this context, it is worth referring to the desire of companies to localize the production of high-margin products in order to ensure immediate delivery to consumers and shorten the time of their stay on the market, taking into account high demand and the need to use FSCW (fast secure coolware) and versioning. Created, in addition to customization, is the deliberate creation of FSCW-based cognitive products. Since cognitive product features significantly improve product value, the loss of these properties is deeply intrusive for the buyer. This, in turn, represents an opportunity for interested research teams to use efficient polynomial optimization to provide keynote papers that lead the international community. At the level of minor features, the application is also a contribution of interesting knowledge, the conclusion of which is linked to the years of refined literature.

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Published

10-10-2024

How to Cite

[1]
Dr. Ayşe Gülcü, “AI-Based Optimization of Manufacturing Processes to Bring Tech Product Production Back to the USA: Strategies and Outcomes”, Australian Journal of Machine Learning Research & Applications, vol. 4, no. 2, pp. 59–85, Oct. 2024, Accessed: Dec. 03, 2024. [Online]. Available: https://sydneyacademics.com/index.php/ajmlra/article/view/143

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