Issue №3, 2019



Planning of coal mining of the fuel and energy enterprise as a random process using the Monte Carlo method


DOI: 10.34130/2070-4992-2019-3-92-98

Full article 

Mezhov S. I. — Altai State University, Barnaul, Russia; Doctor of Economics, Director of the International Institute of Economics, Management and Information Systems, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Cherepanova N. A. — JSC SUEK-Kuzbass, Kemerovo, Russia; financial controller, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Coal mining is traditionally associated with high production risks, to reduce which it is necessary to make maximum management efforts. Security is a fundamental principle of resource corporations and an integral, daily element of their work. The most important problem for coal mining corporations is the high cost of eliminating all types of failures and forced equipment downtime, which reduces financial performance.
The aim of the study is to determine the nature of the correlation effect of random failures on the volume and cost characteristics of coal mining, to develop a scientific approach to forecasting a coal production plan based on simulation modeling.
The methodological basis of the study is the apparatus of the theory of operations research and mathematical modeling. It was found that random failure events with sufficient reliability are described as streams of random events with the Poisson distribution law; the variation in the volumes of coal production with high accuracy obeys the normal distribution law, the parameters of which: mathematical expectation and standard deviation can be determined by retrospective statistics. The use of simulation methods to assess the risks of failures and failures allows you to control several basic variables on the economic efficiency of the plan.
Key findings and results. Managing production risks using Monte Carlo simulations will allow you to combine sensitivity analysis and assessment of scenario options. Sensitivity analysis is characterized by the fact that factors are perceived separately, while in imitation modeling uncertain variables are considered taking into account their interactions. In the structure of the simulation model, the relationships between all variables are specified either functionally or statistically. The tasks of increasing the reliability of the coal mining process, reducing economic losses from accidental failures: accidents, failures of technological equipment due to the need for additional production costs for restoration work have been solved.
The developed methodological provisions for forecasting the coal mining plan are of practical importance and can be used in the practice of making decisions by coal companies.

Keywords: random flow, event, production risk, simulation, failure rate, failure prevention costs, profit, production volume.


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For citation: Mezhov S. I., Cherepanova N. A. Planning of coal mining of the fuel and energy enterprise as a random process using the Monte Carlo method // Corporate governance and innovative economic development of the North: Bulletin of the Research Center of Corporate Law, Management and Venture Capital of Syktyvkar State University. 2019. No. 3. Рр. 92–98. DOI: 10.34130/2070-4992-2019-3-92-98