Articles
The Impact of Machine Learning on Sustainable Manufacturing Practices in the USA: Strategies and Outcomes in Tech Products
Published 18-09-2024
Keywords
- Sustainable Manufacturing,
- Tech Products
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
How to Cite
[1]
Dr. Nisha Singh, “The Impact of Machine Learning on Sustainable Manufacturing Practices in the USA: Strategies and Outcomes in Tech Products”, Journal of AI-Assisted Scientific Discovery, vol. 4, no. 2, pp. 188–211, Sep. 2024, Accessed: Nov. 12, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/157
Abstract
Sustainable manufacturing has become a significant part of the competitive scenario and economic growth efforts in global markets and a constant presence in company everyday decision-making. Current global long-term goals and milestones such as the Sustainable Development Goals (SDGs), aimed at accelerating the transition to a circular economy and the upcoming New US Economy era must be implemented or adopted through substantial changes by manufacturing companies. The COVID-19 pandemic is a raw expression of the severe crisis that can result from a world that has not adapted to more rational use of resources, renewable and non-renewable. Most of the physical characteristics of manufactured products are already structured in the design phase and through market and consumer pressure, the manufacturer's production and decision-making become the factory as a landscape of triggers and levers for change. This new strategic positioning through strategic management and the possibility of obtaining significant benefits through advanced technologies including "intelligent" and "agile" assistance.
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