International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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The Impact of AI in Metallurgy: From Ore Extraction to Smart Manufacturing

Author(s) Richardson Cau
Country United States
Abstract The integration of Artificial Intelligence (AI) into the metallurgy sector has fundamentally transformed the industry, enhancing operational efficiency, sustainability, and the quality of products across various stages of metal production. AI’s application begins with ore extraction, where it assists in the precise identification of ore deposits and optimizes mining operations through autonomous systems and predictive analytics. As the extracted ore is processed, AI technologies enable better control over material processing and smelting, improving energy efficiency and reducing environmental impact. AI-driven smart manufacturing systems are revolutionizing the production phase by facilitating intelligent automation, optimizing resource utilization, and ensuring high-quality outputs. These systems enhance the precision of metal casting, forging, and finishing processes, enabling more efficient production lines. Furthermore, AI's role in predictive maintenance, real-time monitoring, and supply chain management contributes significantly to reducing operational costs and improving overall productivity. While the adoption of AI in metallurgy offers immense benefits, challenges such as high implementation costs, the need for skilled workers, and potential job displacement must be addressed. Despite these challenges, the benefits of AI in metallurgy, particularly in terms of sustainability, cost reduction, and process optimization, make it a critical component of the industry’s future. This article explores the various stages of AI application in metallurgy, from ore extraction to smart manufacturing, providing a comprehensive analysis of its impact on the sector.Artificial Intelligence, Metallurgy, Smart Manufacturing, Process Optimization.
Keywords Artificial Intelligence, Metallurgy, Smart Manufacturing, Process Optimization.
Field Engineering
Published In Volume 7, Issue 2, March-April 2025
Published On 2025-04-08
DOI https://doi.org/10.36948/ijfmr.2025.v07i02.40849
Short DOI https://doi.org/g9fb6z
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