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Artificial Intelligence and Machine Learning In Metallurgy. Part 2. Application Examples

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Metallurgist Aims and scope

The paper offers a detailed description of the application and significance of machine learning methods during various processing stages of modern metallurgy. The relevance of this topic is based on the significant positive technical and economic effects from the use of machine learning noted by both Russian and world-leading manufacturers in the field of metallurgy.

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  1. Bauman Moscow State Technical University, Moscow, Russia

    P. Yu. Zhikharev, A. V. Muntin, D. A. Brayko & M. O. Kryuchkova

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Translated from Metallurg, Vol. 67, No. 10, pp. 99–111, October, 2023. Russian DOIhttps://doi.org/10.52351/00260827_2023_10_99.

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Zhikharev, P.Y., Muntin, A.V., Brayko, D.A. et al. Artificial Intelligence and Machine Learning In Metallurgy. Part 2. Application Examples. Metallurgist 67, 1545–1560 (2024). https://doi.org/10.1007/s11015-024-01648-y

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