Rock Mechanics and Rock Engineering

, Volume 47, Issue 2, pp 757–770 | Cite as

Surface Miners: Evaluation of the Production Rate and Cutting Performance Based on Rock Properties and Specific Energy

  • Chiara Origliasso
  • Marilena Cardu
  • Vladislav Kecojevic
Original Paper

Abstract

The purpose of this research was to evaluate the production rate (PR) and cutting performance of surface miners (SM) based on rock properties and specific energy (SE). We use data from equipment manufacturers and experimental data in this study and propose a new method and equations to determine both the PR and the cutting speed of SM. The unconfined compressive strength (UCS) of the rock, its abrasivity, and the machine’s engine power are the three most important factors influencing the PR. Moreover, the cutting depth, UCS, and engine power have a significant impact on the cutting speed. We propose a new method and equations to determine the energy required to cut a volume unit and a surface unit, i.e., specific energy, and establish the relationship between SE, UCS, and PR. The results of this study can be used by surface miner operators to evaluate the applicability of the machines to a specific mine site.

Keywords

Surface miner Rock properties Specific energy Production rate 

References

  1. Barendsen P (1970) Tunneling with machines working on the undercutting principle. In: Proceedings of the South African Tunneling Conference, Atlanta, pp 53–58Google Scholar
  2. Bilgin N, Balci C, Eskikaya S, Ergunlap D (1997a) Full scale and small scale cutting tests for equipment Selection in a Celestine mine. In: Proceeding of the 6th International Symposium on Mine Planning and Equipment Selection, Wroclaw, pp 387–392Google Scholar
  3. Bilgin N, Kuzu C, Eskikaya S (1997b) Cutting performance of rock hammers and roadheaders in Istanbul Metro drivages. In: Proceeding World Tunnel Congress, Tunnels for People, Balkema, pp 455–460Google Scholar
  4. Dey K, Ghose AK (2008) Predicting “cuttability” with surface miners—a rock-mass classification approach. J Min Met Fuels 56(5–6):85–92Google Scholar
  5. Dey K, Ghose AK (2011) Review of cuttability indices and a new rock-mass classification approach for selection of surface miners. Rock Mech Rock Eng 44(5):601–611. doi: 10.1007/s00603-011-0147-4 CrossRefGoogle Scholar
  6. Eskikaya S, Bilgin N, Ozdemir L et al (2000) Development of rapid excavation technologies for the Turkish mining and tunnelling industries. NATO TU Excavation SfS Programme project report. Istanbul Technical University, Faculty of Mines, Istanbul pp 172Google Scholar
  7. Evans I (1972a) Line spacing of picks for efficient cutting. Int J Rock Mech Min Sci Geomech Abstr 9:355–359CrossRefGoogle Scholar
  8. Evans I (1972b) Relative efficiency of picks and discs for cutting rock. MRDE Report No. 41, National Coal Board, UK, p 6Google Scholar
  9. Evans I (1982) Optimum line spacing for cutting picks. Min Eng 3:433–434Google Scholar
  10. Evans I (1984a) A theory of the cutting force for point attack picks. Int J Min Eng 2:63–71CrossRefGoogle Scholar
  11. Evans I (1984b) Basic mechanics of the point attack pick. Colliery Guardian, London, pp 189–193Google Scholar
  12. Fowell RJ, Johnson ST (1991) Cuttability assessment applied to drag tool tunneling machines. In: Proceeding of the 7th International Congress on Rock Mechanics, A.A. Balkema, Aachen, pp 985–990Google Scholar
  13. Greminger M (1982) Technical Note: experimental studies of the influence of rock anisotropy on size and shape effects in point load testing. Int J Rock Mech Min Sci Geomech Abstr 19:241–246CrossRefGoogle Scholar
  14. Jones IO, Kramadibrata S (1995) An excavating power model for continuous surface miners. Ausimm Proc 300(2):33–40 ISSN: 1034–6783Google Scholar
  15. Nishimatsu Y (1972) The mechanics of the rock cutting. Int J Rock Mech Min Sci Geomech 9:261–271CrossRefGoogle Scholar
  16. Palmström A (1985) Application of the volumetric joint count as a measure of rock mass jointing. Int. Symp. on Fundamentals of Rock Joints, Björkliden, pp 103–110Google Scholar
  17. Plinninger RJ, Spaun G, Thuro K (2002) Prediction and classification of tool wear in drill and blast tunneling, Engineering Geology for Developing Countries—Proceedings of the 9th Congress of the International Association for Engineering Geology and the Environment, Durban, pp 16–20Google Scholar
  18. Plinninger RJ, Kasling H, Thuro K, Spaun G (2003) Testing conditions and geomechanical properties influencing the Cerchar abrasiveness index CAI value. Int J Rock Mech Min Sci 40:259–263CrossRefGoogle Scholar
  19. Pradhan P, Dey K (2009) Rock cutting with surface miner: a computational approach. J Eng Technol Res 1(6):115–121Google Scholar
  20. Rostami J, Ozdemir L et al (1994a) Roadheaders performance optimization for mining and civil construction. In: Proceeding of 13th Annual Technical Conference, Institute of Shaft Drilling Technology (ISDT) Las VegasGoogle Scholar
  21. Rostami J, Ozdemir L, Neil D (1994b) Performance Prediction, The Key Issue in Mechanical Excavation. Mining Engineering, CSM Internal Report, GoldenGoogle Scholar
  22. Roxborough FF, Phillips HR (1975) Rock excavation by disc cutter. Intern J Rock Mech Min Sci Geomech 12(12):361–366CrossRefGoogle Scholar
  23. Thuro K (1997) Drillability prediction—geological influences in hard rock drill and blast tunnelling. Geol Rundsch 86:426–438CrossRefGoogle Scholar
  24. Thuro K, Plinninger RJ (1998) Geological limits in roadheader excavation—four case studies. In: Proceedings of the 8th international association for engineering geology congress, RotterdamGoogle Scholar
  25. Thuro K, Plinninger RJ (1999) Roadheader excavation performance—geological and geotechnical influences. In: Proceedings of the 9th international congress on rock mechanics, ParisGoogle Scholar
  26. West G (1989) Technical note: rock abrasiveness testing for tunnelling. Int J Rock Mech Min Sci Geomech Abstr 26(2):151–160CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Wien 2013

Authors and Affiliations

  • Chiara Origliasso
    • 1
  • Marilena Cardu
    • 2
    • 3
  • Vladislav Kecojevic
    • 4
  1. 1.Department of Mining EngineeringCoassoloItaly
  2. 2.Department of LandEnvironment and Infrastructures (DIATI)TurinItaly
  3. 3.CNR-IGAGTurinItaly
  4. 4.Department of Mining EngineeringWest Virginia University 359C Mineral Resources BuildingMorgantownUSA

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