UDC 338.24: 004.94
DOI: 10.36871/ek.up.p.r.2025.03.01.009
Authors
Olga P. Shevchenko,
Kuban State Agrarian University named after I. T. Trubilin, Krasnodar, Russia
Alexander L. Zolkin,
Volga State University of Telecommunications
and Informatics, Samara, Russia
Julia N. Koval,
Siberian Fire and Rescue Academy of State Firefighting Service of Ministry
of Russian Federation for Civil Defense, Emergencies and Elimination
of Consequences of Natural Disasters, Zheleznogorsk, Russia
Taisiya G. Garbuzova,
Saint-Petersburg State Forest Technical University,
St. Petersburg, Russia
Abstract
The article discusses the main directions of using digital twins, their impact on improving the efficiency of resource management and reducing costs. The authors focus on the integration of digital twins with the technologies of the Internet of Things, big data and artificial intelligence, which make it possible to simulate and predict the operation of production systems in real time. The study presents modern approaches to creating digital twins, as well as analyzes the existing problems of their implementation, including high capital costs, lack of qualified personnel and lack of unified standards. The main conclusions of the article indicate the potential of digital twins in increasing labor productivity, reducing equipment downtime and reducing product defects. The authors conclude that the development of this technology contributes to digital transformation, but an approach is required that includes the development of a regulatory framework, government support and investments in training specialists. The special feature of the work is a systematic analysis of the advantages and problems of introducing digital twins in the Russian economy, as well as a proposal for promising areas of their development.
Keywords
digital twins, production optimization, digital transformation, predictive analytics, artificial intelligence, resource management
