CEO
K-MINE Group
Education
1992: Kryvyi Rih Mining Institute (Kryvyi Rih National University),
1995: Candidate of Technical Sciences,
2007: Doctor of Engineering.
2021: Full Member of the Australasian Institute of Mining and Metallurgy (AusIMM), the Canadian Institute of Mining, Metallurgy and Petroleum (CIM).
Professional Experience
1995: CEO of K-MINE Group
Under his supervision the company has established itself as a leader in the digitization of mining companies based on K-MINE.
Occupational category and interests: integrated software solutions for mining, mathematical modeling of mineral deposits, creation of digital twins for mining companies, mining and geological design works, geological and economic evaluation of deposits, automation of mining and processing of minerals.
Digitization of mining management powered by K-MINE
We know how to plan for business success. Mining operations with K-MINE helps make informed decisions, determine the economic and technical direction of a project and increase the real value of assets.
K-MINE has a modular structure based on a single graphical core, a single database and a set of customized software modules to automate all mining stages in opencast or underground mining. In addition, mining companies can implement the K-MINE automated mining control system at any production stage.
K-MINE makes it possible to simulate different types of mineral deposits in a three-dimensional space. The generated 3D model can further be used to calculate the deposit reserves or its sections during the geological and economic assessment, surveying, designing drilling and blasting operations, determining economically feasible mining boundaries, etc. Digital models of deposits can also be used to calculate scenarios for the development of open pits/mines, automate processes anywhere from planning and design of deposit development and mining to the control of mining equipment repairs. It is possible to generate results as reports based on real-time data used for optimal management decision-making.
The advantage is that the data analysis is performed using special learning algorithms and provides the basis for improving and optimizing production and business processes. As a result, you are able to achieve the maximum effect of managing a digital mining company.