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Development of a Quantitative Assessment Algorithm for Operational Risks in Mining Engineering

Author

Listed:
  • Marina Nevskaya

    (Department of Organization and Management, St. Petersburg Mining University of Empress Catherine II, 199106 St. Petersburg, Russia)

  • Anna Shabalova

    (Department of Organization and Management, St. Petersburg Mining University of Empress Catherine II, 199106 St. Petersburg, Russia)

  • Liubov Nikolaichuk

    (Educational Centre for Digital Technologies, St. Petersburg Mining University of Empress Catherine II, 199106 St. Petersburg, Russia)

  • Natalya Kirsanova

    (Department of Economic Theory, St. Petersburg Mining University of Empress Catherine II, 199106 St. Petersburg, Russia)

Abstract

Whenever any type of ore deposit is developed, it comes with significant risks, such as uncertain reserves, harsh climate conditions, and other uncontrollable factors. To manage these risks effectively, companies need to quickly adapt to changing conditions. This paper presents a method for evaluating risks using a simulation model. The main objective is to identify factors of operational risk and determine the project parameters that have the greatest impact on the probability of a risk event. The method includes the classification of operational risks based on the way they arise; the creation of a risk decomposition matrix dividing risks by production tasks; and the construction of a mathematical model using the identified risk factors. The method was tested by developing a simulation model of an underground mine conveyor network in Anylogic (8.9.2) software. A simulation experiment showed that conveyor shutdowns could result in an 11.23% reduction in annual revenue. Based on the results, recommendations were made on how these risks can be reduced and on the need to implement a transport system to increase resilience.

Suggested Citation

  • Marina Nevskaya & Anna Shabalova & Liubov Nikolaichuk & Natalya Kirsanova, 2025. "Development of a Quantitative Assessment Algorithm for Operational Risks in Mining Engineering," Resources, MDPI, vol. 14(4), pages 1-14, March.
    • Handle: RePEc:gam:jresou:v:14:y:2025:i:4:p:53-:d:1620026
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