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AÇIK OCAK MADENLERİNDE DELME OPERASYONUNDA KULLANILAN DELİCİ UÇLARIN OPTİMUM DEĞİŞTİRME ZAMANININ TAYİNİ

Year 2021, Volume: 60 Issue: 2, 83 - 87, 01.06.2021
https://doi.org/10.30797/madencilik.847142

Abstract

2012 yılından itibaren cevher fiyatlarının düşmesi ile birçok madencilik şirketi operasyonlarını durdurma kararı almıştır. İş hayatında kalabilmek için, bazı maden yöneticileri operasyonel maliyetleri düşürme stratejileri araştırmaya başlamıştır. Bir maliyet unsuru olarak önemi göz önüne alındığında, açık ocak madenlerinde delme verimliliğini ve performansını artırmak, önemli ölçüde tasarruf sağlama potansiyeline sahiptir. Verimlilik ve performans kazanımları, delme operasyonunun izlenmesi, izleme verilerinin istatistiksel araçlarla analiz edilmesi ve operasyonel değişkenlerin optimize edilmesiyle gerçekleştirilebilir. Kontrol edilebilir delme parametrelerinin en iyi konfigürasyonunu bulmak, penetrasyon oranını artırmaya ve delici ucu değiştirme süresini optimize etmeye yardımcı olur, böylece daha az delici uç tüketilir. Bu çalışmada, bir tricone delici ucun optimum değiştirme süresi, bir maliyet minimizasyon problemi olarak formüle edilmiş ve bir genetik algoritma (GA) ile çözülmüştür. Önerilen yaklaşımı göstermek için, kontrol edilebilir değişkenlerin delme performansı üzerindeki etkileri deneysel olarak istatistiksel yöntemlerle ölçülmüş ve optimizasyon için kullanılmıştır. Sonuçlar, önerilen yaklaşımın açık ocak madenlerinde delme uçları için en uygun değiştirme süresini belirlemede kullanılabileceğini göstermektedir.

References

  • AtlasCopco. 2012. Blasthole Drilling in Open Pit Mining. Edited by Atlas Copco Drilling Solutions. Garland, USA.
  • Eren, T., and Ozbayoglu, M. E., 2010. Real time optimization of drilling parameters during drilling operations. SPE Oil and Gas India Conference and Exhibition.
  • Fiscor, S. 2011. New System Manages Main Compressor on Rotary Drills: Engineering and Mining Journal, May 2011, 4.
  • Ghosh, R., Schunnesson, H., and Kumar, U., 2015. The use of specific energy in rotary drilling: the effect of operational parameters. International Symposium on the Application of Computers and Operations Research in the Mineral Industry.
  • Ghosh, R., Schunnesson, H., and Kumar, U., 2016. Evaluation of operating life length of rotary tricone bits using Measurement While Drilling data: International Journal of Rock Mechanics and Mining Sciences, 83:41-48.
  • Hatherly, P., Leung, R., Scheding, S., and Robinson, D., 2015. Drill monitoring results reveal geological conditions in blasthole drilling: International Journal of Rock Mechanics and Mining Sciences, 78:144-154.
  • Irawan, S., Rahman, A. M. A., and Tunio, S. Q., 2012. Optimization of weight on bit during drilling operation based on rate of penetration model: Research Journal of Applied Sciences, Engineering and Technology, 4 (12):1690-1695.
  • Kricak, L., Miljanovic, I., Mitrovic, S., Negovanovic, M., Nuric, A., and Nuric, S., 2015. Development of a fuzzy model for predicting the penetration rate of tricone rotary blasthole drilling in open pit mines: Journal of the Southern African Institute of Mining and Metallurgy, 115 (11):1065-1071.
  • Kumral, M., 2013. Optimizing ore–waste discrimination and block sequencing through simulated annealing: Applied Soft Computing, 8 (13):3737-3744.
  • Kumral, M., and Ozer, U., 2013. Planning additional drilling campaign using two-space genetic algorithm: A game theoretical approach: Computers & geosciences 52:117-125.
  • Montgomery, D. C., 2009. Introduction to statistical quality control, John Wiley & Sons (New York).
  • Motahhari, H. R., Hareland, G., Nygaard, R., and Bond, B., 2009. Method of optimizing motor and bit performance for maximum ROP: Journal of Canadian Petroleum Technology, 48 (06):44-49.
  • Myers, R. H., Montgomery, D. C., and Anderson-Cook, C., 2009. Response surface methodology. Vol. 20, New Jersey, John Wiley & Sons, Inc.
  • Plinninger, R. J., Spaun, G., and Thuro, K., 2002. Predicting tool wear in drill and blast: Tunnels & Tunneling International Magazine, 1-5.
  • Shishvan, M. S., and Sattarvand, J., 2015. "Long term production planning of open pit mines by ant colony optimization: European Journal of Operational Research, 240 (3):825-836.
  • Taheri, A., Qao, Q., and Chanda, E., 2016. Drilling penetration rate estimation using rock drillability characterization index: Journal of the Institution of Engineers (India), Series D 97 (2):159-170.
  • Tail, M., Yacout, S., and Balazinski, M., 2010. Replacement time of a cutting tool subject to variable speed: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 224 (3):373-383.
  • Teale, R., 1965. The concept of specific energy in rock drilling: International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts.
  • Ugurlu, O. F., and Kumral, M., 2020a. Cost optimization of drilling operations in open-pit mines through parameter tuning: Quality Technology & Quantitative Management, 17 (2):173-185.
  • Ugurlu, O. F., and Kumral, M., 2020b. Management of Drilling Operations in Surface Mines Using Reliability Analysis and Discrete Event Simulation: Journal of Failure Analysis and Prevention, 20 (4):1143-1154. doi: 10.1007/s11668-020-00921-x.

DRILL BIT MONITORING AND REPLACEMENT OPTIMIZATION IN OPEN-PIT MINES

Year 2021, Volume: 60 Issue: 2, 83 - 87, 01.06.2021
https://doi.org/10.30797/madencilik.847142

Abstract

Since 2012, low commodity prices have forced many mining companies to suspend or cease operations. To remain in business, some mine managers are exploring strategies to reduce operational costs. Given its importance as a cost element, increasing bench drilling efficiency and performance in open-pit mines has the potential to generate considerable savings. Efficiency and performance gains can be realized by monitoring the drilling operation, analyzing monitoring data with statistical tools and optimizing operational variables. Finding the best configuration of controllable drilling parameters would help to increase penetration rate and optimize drill bit replacement time so that fewer drill bits are consumed. In this paper, the optimal replacement time of a tricone drill bit is formulated as a cost minimization problem and solved by a genetic algorithm (GA). To demonstrate the proposed approach, the effects of controllable variables on drilling performance are experimentally quantified by statistical methods and used for optimization. Results show that the proposed approach can be used to determine the optimal replacement time for drill bits in open-pit mines.

References

  • AtlasCopco. 2012. Blasthole Drilling in Open Pit Mining. Edited by Atlas Copco Drilling Solutions. Garland, USA.
  • Eren, T., and Ozbayoglu, M. E., 2010. Real time optimization of drilling parameters during drilling operations. SPE Oil and Gas India Conference and Exhibition.
  • Fiscor, S. 2011. New System Manages Main Compressor on Rotary Drills: Engineering and Mining Journal, May 2011, 4.
  • Ghosh, R., Schunnesson, H., and Kumar, U., 2015. The use of specific energy in rotary drilling: the effect of operational parameters. International Symposium on the Application of Computers and Operations Research in the Mineral Industry.
  • Ghosh, R., Schunnesson, H., and Kumar, U., 2016. Evaluation of operating life length of rotary tricone bits using Measurement While Drilling data: International Journal of Rock Mechanics and Mining Sciences, 83:41-48.
  • Hatherly, P., Leung, R., Scheding, S., and Robinson, D., 2015. Drill monitoring results reveal geological conditions in blasthole drilling: International Journal of Rock Mechanics and Mining Sciences, 78:144-154.
  • Irawan, S., Rahman, A. M. A., and Tunio, S. Q., 2012. Optimization of weight on bit during drilling operation based on rate of penetration model: Research Journal of Applied Sciences, Engineering and Technology, 4 (12):1690-1695.
  • Kricak, L., Miljanovic, I., Mitrovic, S., Negovanovic, M., Nuric, A., and Nuric, S., 2015. Development of a fuzzy model for predicting the penetration rate of tricone rotary blasthole drilling in open pit mines: Journal of the Southern African Institute of Mining and Metallurgy, 115 (11):1065-1071.
  • Kumral, M., 2013. Optimizing ore–waste discrimination and block sequencing through simulated annealing: Applied Soft Computing, 8 (13):3737-3744.
  • Kumral, M., and Ozer, U., 2013. Planning additional drilling campaign using two-space genetic algorithm: A game theoretical approach: Computers & geosciences 52:117-125.
  • Montgomery, D. C., 2009. Introduction to statistical quality control, John Wiley & Sons (New York).
  • Motahhari, H. R., Hareland, G., Nygaard, R., and Bond, B., 2009. Method of optimizing motor and bit performance for maximum ROP: Journal of Canadian Petroleum Technology, 48 (06):44-49.
  • Myers, R. H., Montgomery, D. C., and Anderson-Cook, C., 2009. Response surface methodology. Vol. 20, New Jersey, John Wiley & Sons, Inc.
  • Plinninger, R. J., Spaun, G., and Thuro, K., 2002. Predicting tool wear in drill and blast: Tunnels & Tunneling International Magazine, 1-5.
  • Shishvan, M. S., and Sattarvand, J., 2015. "Long term production planning of open pit mines by ant colony optimization: European Journal of Operational Research, 240 (3):825-836.
  • Taheri, A., Qao, Q., and Chanda, E., 2016. Drilling penetration rate estimation using rock drillability characterization index: Journal of the Institution of Engineers (India), Series D 97 (2):159-170.
  • Tail, M., Yacout, S., and Balazinski, M., 2010. Replacement time of a cutting tool subject to variable speed: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 224 (3):373-383.
  • Teale, R., 1965. The concept of specific energy in rock drilling: International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts.
  • Ugurlu, O. F., and Kumral, M., 2020a. Cost optimization of drilling operations in open-pit mines through parameter tuning: Quality Technology & Quantitative Management, 17 (2):173-185.
  • Ugurlu, O. F., and Kumral, M., 2020b. Management of Drilling Operations in Surface Mines Using Reliability Analysis and Discrete Event Simulation: Journal of Failure Analysis and Prevention, 20 (4):1143-1154. doi: 10.1007/s11668-020-00921-x.
There are 20 citations in total.

Details

Primary Language English
Journal Section Research Article
Authors

Ömer Faruk Uğurlu 0000-0002-5817-3268

Publication Date June 1, 2021
Submission Date December 25, 2020
Published in Issue Year 2021 Volume: 60 Issue: 2

Cite

APA Uğurlu, Ö. F. (2021). DRILL BIT MONITORING AND REPLACEMENT OPTIMIZATION IN OPEN-PIT MINES. Bilimsel Madencilik Dergisi, 60(2), 83-87. https://doi.org/10.30797/madencilik.847142
AMA Uğurlu ÖF. DRILL BIT MONITORING AND REPLACEMENT OPTIMIZATION IN OPEN-PIT MINES. Mining. June 2021;60(2):83-87. doi:10.30797/madencilik.847142
Chicago Uğurlu, Ömer Faruk. “DRILL BIT MONITORING AND REPLACEMENT OPTIMIZATION IN OPEN-PIT MINES”. Bilimsel Madencilik Dergisi 60, no. 2 (June 2021): 83-87. https://doi.org/10.30797/madencilik.847142.
EndNote Uğurlu ÖF (June 1, 2021) DRILL BIT MONITORING AND REPLACEMENT OPTIMIZATION IN OPEN-PIT MINES. Bilimsel Madencilik Dergisi 60 2 83–87.
IEEE Ö. F. Uğurlu, “DRILL BIT MONITORING AND REPLACEMENT OPTIMIZATION IN OPEN-PIT MINES”, Mining, vol. 60, no. 2, pp. 83–87, 2021, doi: 10.30797/madencilik.847142.
ISNAD Uğurlu, Ömer Faruk. “DRILL BIT MONITORING AND REPLACEMENT OPTIMIZATION IN OPEN-PIT MINES”. Bilimsel Madencilik Dergisi 60/2 (June 2021), 83-87. https://doi.org/10.30797/madencilik.847142.
JAMA Uğurlu ÖF. DRILL BIT MONITORING AND REPLACEMENT OPTIMIZATION IN OPEN-PIT MINES. Mining. 2021;60:83–87.
MLA Uğurlu, Ömer Faruk. “DRILL BIT MONITORING AND REPLACEMENT OPTIMIZATION IN OPEN-PIT MINES”. Bilimsel Madencilik Dergisi, vol. 60, no. 2, 2021, pp. 83-87, doi:10.30797/madencilik.847142.
Vancouver Uğurlu ÖF. DRILL BIT MONITORING AND REPLACEMENT OPTIMIZATION IN OPEN-PIT MINES. Mining. 2021;60(2):83-7.

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