M.N. Belozyorov1, A.N. Smirnov2
1 National Research Technological University «MISIS» (Moscow, Russia)
2 Sberbank of Russia PJSC (Moscow, Russia)

1 mnbelozyorov@gmail.com, 2 asmirnov889@yandex.ru

Modern production, whether mixing, separation or cutting, is characterized by the presence of many material and technological flows. This leads to a wide variety of formulations that determine the composition and properties of the final product. The purpose of the study is to develop component schemes of a multiscene digital twin to solve the problem of production planning.

Variants of component schemes of a multi-scenario digital twin with an optimizer, procurement management components, machine learning, as well as a digital twin scheme that includes technological processes of production and operation in the perimeter of coverage have been developed.

The practical significance of this work is optimization of production to minimize waste. The proposed approach has been tested in the processes of managing the Sberbank of Russia’s model risk. Individual elements of this approach have been tested in companies of the food and metallurgical industries.

Belozyorov M.N., Smirnov A.N. Component schemes of a multiscene digital twin for solving production planning tasks. Neurocomputers. 2025. V. 27. № 4. P. 72–80. DOI: https://doi.org/10.18127/j19998554-202504-07 (in Russian)

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