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Scientific, Technological and Production Journal
ISSN 2079–3332 (print)
ISSN 3034-6835 (online)
founded in 2001

The digital twin technology and its application for mining industry

Original articles: 2024 No 5

The digital twin technology and its application for mining industry

DOI: 10.56195/20793332_2024_5_38_43

Read in pdf I. V. Artemov, M. B. Nosyrev
  1. Ural State Mining University, Yekaterinburg, Russian Federation
p. 38-43, No.5/2024
Abstract:
The material production is a main component in almost any kind of economy. It is always a high-tech industry, that must meet the requirements of efficiency, performance and competitiveness. To satisfy all these demands the material industry often needs to be transformed into digital industry. This process consists of the development and application of digital platforms, digital twins of real objects and processes, as well as the transition to cyber-physical systems. These global changes are accompanied by the development of fundamentally new business processes and business models at all levels. The development and application of digital twins is an advanced technology (although it is based on quite old ideas), it is an integrator of “end-to-end” digital technologies and new production capabilities (primarily digital design and modeling). It provides a significant contribution to the creation of globally competitive next-generation products in the shortest possible time. Research results: In this article we present a description of Digital Twin term in its diversity. Multiple kinds of digital twin’s classification were given and also we introduce many examples of this technology’s usage in mining industry.
Keywords:
digital twin, digital transformation, mining industry, 3D-model, process model
For citation:
Artemov I. V., Nosyrev M. B. The digital twin technology and its application for mining industry. Mine Surveying and Subsurface Use. 2024;(5):38-43. (In Russ.). https://doi.org/10.56195/20793332_2024_5_38_43.
Information about the authors:
  1. Ivan V. Artemov – specialist, postgraduate student, direction of Artificial Intelligence and Machine Learning, Ural State Mining University, Yekaterinburg, Russian Federation, Scopus Author ID: 57022242500, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
  2. Mikhail B. Nosyrev – Dr. Sci. (Eng.), Prof., Ural State Mining University, Yekaterinburg, Russian Federation, Scopus Author ID:57194022210, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
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