Digitalization and Forecasting of the Iron Ore Business

Stanislav Popov, Stanislav Popov, Denys Kolosovskyi, Michael Radin, Liudmyla Shokotko, Oleksandr Astafiev

2022

Abstract

Ukraine’s iron ore mining industry is among the most powerful ones in the world, which account for 90% of the volume of iron ore products. All iron ore mining enterprises of Ukraine are private. Current conditions of their operation and prospects for its development bring up the problem of the most accurate forecasting of economic results of mining by implementation of its key process – ore stoping. This determines profitability of the business, its competitiveness and possibility of reasonable planning. To solve this problem, the authors developed a methodology, a system of technical and economic indicators and a computer program to provide multifactor economic analysis of competitive solutions on stoping and selection of optimal one according to the forecast economic results of its application. Use of ore value indicators, the value of ore reserves and the degree of use of the value as a result of stoping makes the basis of this methodology and the system of indicators. Further development of this work implies creation of systems for modeling the entire process of underground iron ore mining the key element of which is stoping with forecasting profitability of the business based on analysis of iron ore market conditions.

Paper Citation

in Harvard Style

Popov S., Kolosovskyi D., Radin M., Shokotko L. and Astafiev O. (2022). Digitalization and Forecasting of the Iron Ore Business. In Proceedings of the 5th International Scientific Congress Society of Ambient Intelligence - Volume 1: ISC SAI, ISBN 978-989-758-600-2, pages 219-229. DOI: 10.5220/0011348400003350

in Bibtex Style

@conference{isc sai22,
author={Stanislav Popov and Denys Kolosovskyi and Michael Radin and Liudmyla Shokotko and Oleksandr Astafiev},
title={Digitalization and Forecasting of the Iron Ore Business},
booktitle={Proceedings of the 5th International Scientific Congress Society of Ambient Intelligence - Volume 1: ISC SAI,},
year={2022},
pages={219-229},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011348400003350},
isbn={978-989-758-600-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Scientific Congress Society of Ambient Intelligence - Volume 1: ISC SAI,
TI - Digitalization and Forecasting of the Iron Ore Business
SN - 978-989-758-600-2
AU - Popov S.
AU - Kolosovskyi D.
AU - Radin M.
AU - Shokotko L.
AU - Astafiev O.
PY - 2022
SP - 219
EP - 229
DO - 10.5220/0011348400003350