Applications of simulation modeling in mining project risk management: criteria, algorithm, evaluation

Marina Nevskaya, Anna Shabalova, Tatyana Kosovtseva, Lybov Nikolaychuk

Article ID: 5375
Vol 8, Issue 8, 2024

VIEWS - 19 (Abstract) 9 (PDF)

Abstract


Project risk management in the mining industry is necessary to identify, analyze and reduce uncertainty. The engineering features of mining enterprises, by their nature, require improved risk management tools. This article proves the relevance of creating a simulation model of the production process to reduce uncertainty when making investment decisions. The purpose of the study is to develop an algorithm for deciding on the economic feasibility of creating a simulation experiment. At the same time, the features and patterns of the cases for which the simulation experiment was carried out were studied. Criteria for feasibility assessment of the model introduction based on a qualitative parameters became the central idea for algorithm. The relevance of the formulated algorithm was verified by creating a simulation model of a potassium salt deposit with subsequent optimization of the production process parameters. According to the results of the experiment, the damage from the occurrence of a risk situations was estimated as a decrease in conveyor productivity by 32.6%. The proposed methods made it possible to minimize this risk of stops in the conveyor network and assess the lack of income due to the risk occurrences.


Keywords


digital technology; risk mitigation measures; mining enterprise; scenario analysis; potassium salt

Full Text:

PDF


References


Babyr, N., & Babyr, K. (2021). To improve the contact adaptability of mechanical roof support. E3S Web of Conferences, 266, 03015. https://doi.org/10.1051/e3sconf/202126603015

Baryannis, G., Validi, S., Dani, S., et al. (2018). Supply chain risk management and artificial intelligence: state of the art and future research directions. International Journal of Production Research, 57(7), 2179–2202. https://doi.org/10.1080/00207543.2018.1530476

Belsky, A. A., & Glukhanich, D. Y. (2023). Standalone power system with photovoltaic and thermoelectric installations for power supply of remote monitoring and control stations for oil pipelines. Renewable Energy Focus, 47, 100493. https://doi.org/10.1016/j.ref.2023.100493

Cerna, G. P., González, J. C., Troncoso-Palacio, A., et al. (2023). Using Discrete Event Simulation to Muck Development Planning in Underground Mining. Procedia Computer Science, 220, 916–921. https://doi.org/10.1016/j.procs.2023.03.125

Cherepovitsyn, A., Tcvetkov, P., & Evseeva, O. (2021). Critical analysis of methodological approaches to assessing sustainability of arctic oil and gas projects. Записки Горного Института, 249, 463–479. https://doi.org/10.31897/pmi.2021.3.15

Dirani, F., & Ponomarenko, T. (2021). Contractual Systems in the Oil and Gas Sector: Current Status and Development. Energies, 14(17), 5497. https://doi.org/10.3390/en14175497

Fedorova, E., Pupysheva, E., & Morgunov, V. (2022). Modelling of Red-Mud Particle-Solid Distribution in the Feeder Cup of a Thickener Using the Combined CFD-DPM Approach. Symmetry, 14(11), 2314. https://doi.org/10.3390/sym14112314

Friederich, J., Lugaresi, G., Lazarova-Molnar, S., et al. (2022). Process Mining for Dynamic Modeling of Smart Manufacturing Systems: Data Requirements. Procedia CIRP, 107, 546–551. https://doi.org/10.1016/j.procir.2022.05.023

Gabov, V. V., Babyr, N. V., & Zadkov, D. A. (2021). Mathematical modelling of operation of the hydraulic support system of the powered support sections with impulse-free continuous regulation of its resistance to the roof rock lowering. IOP Conference Series: Materials Science and Engineering, 1064(1), 012045. https://doi.org/10.1088/1757-899x/1064/1/012045

Golovina, E., Khloponina, V., Tsiglianu, P., et al. (2023). Organizational, Economic and Regulatory Aspects of Groundwater Resources Extraction by Individuals (Case of the Russian Federation). Resources, 12(8), 89. https://doi.org/10.3390/resources12080089

Gong, H., Moradi Afrapoli, A., & Askari-Nasab, H. (2023). Integrated simulation and optimization framework for quantitative analysis of near-face stockpile mining. Simulation Modelling Practice and Theory, 128, 102794. https://doi.org/10.1016/j.simpat.2023.102794

Huerta, J. R., Silva, R. S., De Tomi, G., et al. (2022). A dynamic simulation approach to support operational decision-making in underground mining. Simulation Modelling Practice and Theory, 115, 102458. https://doi.org/10.1016/j.simpat.2021.102458

Ivanov, S., Knyazkina, V., & Myakotnykh, A. (2021). Recording gear-type pump acoustic signals for assessing the hydraulic oil impurity level in a hydraulic excavator transmission. E3S Web of Conferences, 326, 00014. https://doi.org/10.1051/e3sconf/202132600014

Kamel, A., Elwageeh, M., Bonduà, S., et al. (2023). Evaluation of mining projects subjected to economic uncertainties using the Monte Carlo simulation and the binomial tree method: Case study in a phosphate mine in Egypt. Resources Policy, 80, 103266. https://doi.org/10.1016/j.resourpol.2022.103266

Koteleva, N. I., Valnev, V. V., & Korolev, N. A. (2023). Augmented reality as a means of metallurgical equipment servicing. Tsvetnye Metally, 4, 14–23. https://doi.org/10.17580/tsm.2023.04.02

Kruk, M. N., Nikulina, A. Yu., & Simonchuk, V. D. (2020). Corporate Social Responsibility Programs for Arctic Companies to Attract Young People. III International Theoretical and Practical Conference “The Crossroads of the North and the East (Methodologies and Practices of Regional Development).” https://doi.org/10.32743/nesu.cross.2020.114-126

Li, S., You, M., Li, D., et al. (2022). Identifying coal mine safety production risk factors by employing text mining and Bayesian network techniques. Process Safety and Environmental Protection, 162, 1067–1081. https://doi.org/10.1016/j.psep.2022.04.054

Matrokhina, K., Trofimets, V., Mazakov, E., et al. (2023). Development of methodology for scenario analysis of investment projects of enterprises of the mineral resource complex. Journal of Mining Institute, 259, 112–124. https://doi.org/10.31897/pmi.2023.3

Mostafaei, K., Maleki, S., Zamani Ahmad Mahmoudi, M., et al. (2022). Risk management prediction of mining and industrial projects by support vector machine. Resources Policy, 78, 102819. https://doi.org/10.1016/j.resourpol.2022.102819

Nazarychev, A. N., Dyachenok, G., Sychev, Y. (2023). A reliability study of the traction drive system in haul trucks based on failure analysis of their functional parts. Journal of Mining Institute, 261, 363-373. https://doi.org/10.00000/PMI.2023.0

Nepsha, F., Voronin, V., Liven, A., et al. (2023). Feasibility study of using cogeneration plants at Kuzbass coal mines. Journal of Mining Institute, 259, 141–150. https://doi.org/10.31897/pmi.2023.2

Pournader, M., Ghaderi, H., Hassanzadegan, A., et al. (2021). Artificial intelligence applications in supply chain management. International Journal of Production Economics, 241, 108250. https://doi.org/10.1016/j.ijpe.2021.108250

Serzhan, S. L., Skrebnev, V. I., & Malevanny, D. V. (2023). Study of the effects of steel and polymer pipe roughness on the pressure loss in tailings slurry hydrotransport. Obogashchenie Rud, 4, 41–49. https://doi.org/10.17580/or.2023.04.08

Shabalov, M. Yu., Zhukovskiy, Yu. L., Buldysko, A. D., et al. (2021). The influence of technological changes in energy efficiency on the infrastructure deterioration in the energy sector. Energy Reports, 7, 2664–2680. https://doi.org/10.1016/j.egyr.2021.05.001

Snopkowski, R., & Napieraj, A. (2012). Method of the production cycle duration time modeling within hard coal longwall faces. Archives of Mining Sciences, 57(1), 121–138. https://doi.org/10.2478/v10267-012-0009-2

Voznyak, O., Spodyniuk, N., Savchenko, O., et al. (2021). Enhancing energetic and economic efficiency of heating coal mines by infrared heaters. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, 2, 104–109. https://doi.org/10.33271/nvngu/2021-2/104

Xiong, Y., Qi, H., Li, Z., et al. (2023). Where risk, where capability? Building the emergency management capability structure of coal mining enterprises based on risk matching perspective. Resources Policy, 83, 103695. https://doi.org/10.1016/j.resourpol.2023.103695

Zhang, L., & Ponomarenko, T. (2023). Directions for Sustainable Development of China’s Coal Industry in the Post-Epidemic Era. Sustainability, 15(8), 6518. https://doi.org/10.3390/su15086518

Zhang, Y., Oldenburg, C. M., Zhou, Q., et al. (2022). Advanced monitoring and simulation for underground gas storage risk management. Journal of Petroleum Science and Engineering, 208, 109763. https://doi.org/10.1016/j.petrol.2021.109763

Zhukovskiy, Y., Korolev, N., & Malkova, Y. (2022). Monitoring of grinding condition in drum mills based on resulting shaft torque. Journal of Mining Institute, 256, 686–700. https://doi.org/10.31897/pmi.2022.91




DOI: https://doi.org/10.24294/jipd.v8i8.5375

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Marina Nevskaya, Anna Shabalova, Tatyana Kosovtseva, Lybov Nikolaychuk

License URL: https://creativecommons.org/licenses/by/4.0/

This site is licensed under a Creative Commons Attribution 4.0 International License.