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Digital twin of an energy-efficient mining enterprise with carbon footprint forecasting

Faxriddin BarakayevNavoi State University of Mining and TechnologiesNafisa MansurovaBukhara State Technical UniversityКамолиддин АбдуллаевTermez State University of Engineering and Agro-TechnologyGulnoza RayimdjanovaThe Institute of History of The Academy of Sciences of The Republic of UzbekistanShakhnoza KhayitovaSamarkand State Medical University
2026
ABI

Annotatsiya

A digital-twin framework is proposed for evaluating energy use and carbon emissions at a mining enterprise. The framework links production and equipment data from Industrial Internet of Things sources with process models and a forecasting module. Its purpose is to relate operating conditions to electricity and fuel consumption and, in turn, to changes in CO 2 emissions. The approach is illustrated with open production and energy data from mining enterprises in Uzbekistan and with several operating scenarios, including increased output and improved energy efficiency.

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