UDC 658.7: 004.8
DOI: 10.36871/ek.up.p.r.2026.05.01.019

Authors

Sofya D. Tikhomirova,
Lyubov P. Sazhneva,
ITMO National Research University, Saint Petersburg, Russia

Abstract

The article is devoted to topical issues of digital transformation of warehouse logistics of metallurgical enterprises based on the integration of artificial intelligence technologies. The necessity of overcoming the limitations of traditional ERP and WMS systems, which do not provide an adequate level of adaptability and intellectual support for management decisions in conditions of high complexity of material flows and demand dynamics, is substantiated. Based on the systematization of scientific approaches, the key areas of digitalization are analyzed: automation of warehouse operations, the Internet of Things, digital twins and artificial intelligence. It has been revealed that the use of machine learning algorithms, computer vision and predictive analytics makes it possible to increase the accuracy of demand forecasting to 90-95%, reduce excess inventory by 15-22% and reduce order processing time by 25-30%. It has been established that existing implementation strategies (complex automation or fragmented use of digital tools) do not allow achieving a systemic effect. An integration approach is proposed as a promising solution, which involves the phased introduction of AI modules into the existing IT infrastructure of metallurgical companies, which ensures a balance between technological development and economic efficiency without the need for a complete modernization of warehouse systems.

Keywords

digital transformation, warehouse logistics, metallurgical industry, artificial intelligence, Industry 4.0, Internet of Things, digital twins, inventory management, optimization of logistics processes

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