Analysis of the key performance indicators between lithologies on Mine to Crusher

• Autorzy: Figueiredo Janine , Torres Vidal , Cruz Rodolfo , Moreira Douglas

Identyfikatory

DOI

10.46873/2300-3960.1417

• Języki publikacji: EN

Abstrakty

EN

The evolution of the mineral economy requires greater technological developments to find a better use of resources and reserves through the relationships between the characteristics of the rocks and the need to enable the entire mining enterprise. This study focuses on the development of new rock blasting technologies that result in a more optimized fragmentation according to the lithology in the feed of the primary crusher. This methodology is known as Mine to Crusher, through which it becomes possible to minimize costs in the future prospecting of the mine and maximize productivity. For this methodology to be developed, it was necessary to implement the Mine to Crusher model. Through this project, the key performance indicators (KPIs), such as average productivity, availability and utilization of the equipment, and a nominal capacity observed in the crushing circuit, were analyzed. Furthermore, by observing the results, it became possible to evaluate the KPIs must be adjusted for better equipment performance and better development and planning of the mining project. Through this project, it was possible to carry out a probabilistic analysis of the project's KPIs using a Monte Carlo simulation. At the end of the work, it became possible to verify the relationship between more compact and less compact lithologies, where there is a difference in results depending on the lithology and properties evaluated. At the end of the evaluations, a difference in the penetration rate and productivity between the CI and FI lithologies of 26.99% and 26.78% respectively was verified. It is also possible to verify that when carrying out sensitivity tests for lithologies, friable lithologies require a reduction in a fixed time of 6%, whereas more compact lithologies require an increase of up to 2% in their time.

Słowa kluczowe

EN

mining operations; hard rock; productivity; Monte Carlo

PL

prace górnicze; skała zwięzła; produktywność; Monte Carlo

• Wydawca: Elsevier ; Główny Instytut Górnictwa
• Czasopismo: Journal of Sustainable Mining
• Rocznik: 2024
• Tom: Vol. 23, iss. 3
• Strony: 214--227
• Opis fizyczny: Bibliogr. 29 poz.

Twórcy

autor

Figueiredo Janine

• Instituto Tecnológico Vale, Ouro Preto 35400-000, MG, Brazil

• https://orcid.org/0000-0003-1396-7889

autor

Torres Vidal

• Instituto Tecnológico Vale, Ouro Preto 35400-000, MG, Brazil

• https://orcid.org/0000-0002-4262-0916

autor

Cruz Rodolfo

• Vale S/A, Serra do Esmeril, Itabira 35900-900, MG, Brazil

• https://orcid.org/0000-0001-7890-6433

autor

Moreira Douglas

• Instituto Tecnológico Vale, Ouro Preto 35400-000, MG, Brazil

• https://orcid.org/0000-0003-4208-9800

Bibliografia

• [1] METSO AUTOTEC. Entenda como o desmonte influencia na britagem. 2019. https://www.mogroup.com/pt/insights/blog/agregados/entenda-como-o-desmonte-influencia-na-britagem/.
• [2] Oliveira AKPA. Modelação integrada - simulação de oper- ações de desmonte - processamento de recursos minerais [dissertation]. Porto: Faculdade de Engenharia, Universidade do Porto; 2020.
• [3] Mohammad R, Mostafa A, Abbas M, Mohammad FH. Prediction of representative deformation modulus of longwall panel roof rock strata using mamdani fuzzy system. Int J Min Sci Technol 2015;25:23-30. https://doi.org/10.1016/j.ijmst.2014.11.007.
• [4] Bameri A, Seifabad MC, Hoseinie SH. Uncertainty consideration in rock mass blastability assessment in open pit mines using Monte Carlo simulation. In: Physics of rocks and processes: eurasian mining; 2021. p. 4. https://doi.org/10.17580/em.2021.01.07.
• [5] Amnieh HB, Bidgoli MH, Mokhtari H, Bazzazi A. Application of simulated annealing for optimization of blasting costs due to air overpressure constraints in open-pit mines. Journal of Mining and Environment 2019;10(4):15. https://doi.org/10.22044/jme.2019.8084.1675.
• [6] Coronado PPV, Tenorio VO. Optimization of open pit haulage cycle using a KPI controlling alert system and a discrete-event operations simulator. Proceedings of international symposium on application of computers and operations research in the mineral industry, vol. 37. APCOM; 2015. p. 23-7.
• [7] Santos JVC. Analise - acompanhamento do desempenho dos equipamentos de transporte da mineradora Ferro+ miner- ação com o KPI movimentado cheio/movimentado vazio [monography]. Universidade Federal de Ouro Preto; 2021.
• [8] Cacceta L, Hill SP. An application of branch and cut to open pit mine scheduling. J Global Optim 2003;27:349-65. https://doi.org/10.1023/A:1024835022186.
• [9] O’Neill MJ. The workplace performance measurement process. In: Taylor & Francis. 2nd ed. Florida: CRC Press; 2007.
• [10] Nader B, Tomi G, Passos AO. Key performance indicators and the mineral value chain integration. REM 2012;65(4): 537-42. https://doi.org/10.1590/S0370-44672012000400015.
• [11] Dougall AW, Mmola TM. Identification of key performance areas in the southern African surface mining delivery environment. J South Afr Inst Min Metall 2015;115:1001-6. https://doi.org/10.17159/2411-9717/2015/v115n11a3.
• [12] Brandão R, Tomi G. Metodologia para estimativa - gestão da produtividade de lavra. REM 2011;64:77-83. https://doi.org/10.1590/S0370-44672011000100010.
• [13] Hartman HL. SME mining engineering handbook. Littleton, Colorado: Aime; 1992.
• [14] Santana IV, Lima MA, Costa LV, Bonfim RJ. Tecnologias aplicadas ao desmonte de rochas. Proceedings of the 1° Simpósio de TCC, FINOM - TECSOMA, vol. 1; 2019. p. 865-82.
• [15] Mahdiyar A, Armaghani DA, Koopialipoor M, Headayat A, Abdullah A, Yahya K. Practical risk assessment of ground vibrations resulting from blasting, using gene expression programming and Monte Carlo simulation techniques. Appl Sci 2020;10(2):17. https://doi.org/10.3390/app10020472.
• [16] Saeidi O, Torabi SR, Ataei M, Rostami J. A stochastic penetration rate model for rotary drilling in surface mines. IJRMMS 2014;68:10. https://doi.org/10.1016/j.ijrmms.2014.02.007.
• [17] Ghasemi E, Sari M, Ataei M. Development of an empirical model for predicting the effects of controllable blasting parameters on flyrock distance in surface mines. IJRMMS 2012;52:7. https://doi.org/10.1016/j.ijrmms.2012.03.011.
• [18] Jiyao G, Sijang W. Study on excavation period estimation of deep hole presplitting blasting based on Monte Carlo. JCEUP 2022;4(3). https://doi.org/10.23977/jceup.2022.040310.
• [19] Silva CR, Souza VCG, Koppe JC. Methodology for determining rom size distribution. REM 2014;67(4):405-12. https://doi.org/10.1590/0370-44672014670184.
• [20] Mariano RM. Determinação de parâmetros geométricos no desmonte de rochas para itabiritos compactos [monography]. Universidade Federal de Ouro Preto; 2018.
• [21] Caterpillar. Cat R MD6420. 2012. https://s7d2.scene7.com/is/content/Caterpillar/C10590939. [Accessed 1 September 2022].
• [22] Fattahi H, Shojaee S, Farsangi MAE, Mansouri H. Hybrid Monte Carlo simulation and ANFIS-subtractive clustering method for reliability analysis of the excavation damaged zone in underground spaces. Comput Geotech 2013;54:11. https://doi.org/10.1016/j.compgeo.2013.07.010.
• [23] Guazzelli SR. Analise de custos de perfuraçao - desmonte em mina de ferro [dissertation]. Universidade Federal de Rio Grande do Sul; 2013.
• [24] Quaglio AO. Otimização da perfuraçao - a segurança nos desmonte de agregado através dos sistemas laser profile - Borestk [dissertation]. Universidade Federal de Ouro Preto; 2003.
• [25] Upadhyay SP, Askari-Nasab H. Simulation and optimization approach for uncertainty-based short-term planning in open pit mines. Int J Min Sci Technol 2018;28:153-66. https://doi.org/10.1016/j.ijmst.2017.12.003.
• [26] Chaves A. Teoria - Pratica de Tratamento de Minérios. 2nd ed. São Paulo: Signus; 2004.
• [27] Oliveira DBM. Projeto de melhoria de fragmentação em desmonte de rochas [monography]. Universidade Federal de Ouro Preto; 2017.
• [28] Zacarias CM. Classificação de maciços rochosos da mina do cérrego do meio aplicada as operações de perfuração [dissertation]. Universidade Federal de Minas Gerais; 2003.
• [29] Menezes DA. Caracterizaçao geotecnica - analise dos modos de ruptura de taludes operacionais em Itabirito compacto [dissertation]. Universidade Federal de Ouro Preto; 2013.