Application of Combined Machine Learning Methods in Metallurgy FOR Analysis, Selection of Materials and Prediction of Properties

In this article, the authors consider the possibility of using combined machine learning methods in metallurgy for analysis, selection of materials, and prediction of properties. The authors analyze various approaches to using machine learning in modern metallographic analysis, establish empirical dependencies, predict properties, and select materials. We will discuss the problems associated with using these methods, offer possible solutions, and analyze key aspects of their implementation. We will also examine the advantages and disadvantages of machine learning use in metallurgy, as well as discuss prospects for its development. This article is a valuable resource for metallurgists who want to incorporate modern technologies into their research and development.