Mining of Mineral Deposits

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Analytical platform to provide competitiveness of ore-mining machinery manufacturing

Olena Parshyna1, Yurii Parshyn1

1Dnipropetrovsk State University of Internal Affairs, Dnipro, 49005, Ukraine

Min. miner. depos. 2020, 14(3):61-70

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      Purpose is to develop analytical platform providing competitiveness of ore-mining machinery manufacturing.

      Methods. The analytical platform combines five modular blocks. It involves determination of an area of optimum process conditions for each tool – part pair. Studies of processibillity by means of cutting were carried out in a production environment of NKMZ CJSC using parts of a spindle type made of 38ХН3МFА steel. For the experiments, cutters, made of different tool materials were prepared; they were turned by means of a diamond disc with the provision of definite geometric parameters. The parts were cut using a chasing lathe1А680 with no cooling. Flank wear was assumed as a criterion of cutter bluntness.

      Findings. Correlations of operating procedures of ore-mining machinery part processing have been identified. Among other things, regularities of wear bit have been defined taking into consideration the influence on accuracy and quality of the surface under processing depending upon the manufacturing system stiffness as well as upon the conditions of fixing of the parts during the tooling. Methods have been developed to define safety margin of the manufacturing system making it possible to show reserves for the improvement of competitiveness of ore-mining machinery production in view of the specified accuracy and processing quality limits. Mathematical models have been developed which practical use helps determine areas of optimum modes of ore-mining equipment part machining; and represent comparative characteristic of procedures taking into consideration processing accuracy and wear impact on the dimensional stability of a cutter.

      Originality.It has been substantiated scientifically that the area of optimum modes is identified in terms of the system totality of the proposed criteria inclusive of the specified indices of quality, accuracy, and efficiency of procedures to process parts of ore-mining machines.

      Practical implications. The identified regularities are analytical framework to make decisions providing manufacturing competitiveness owing to optimization of procedure as well as to the improvement of accuracy, processing quality, and functional reliability of the parts of ore-mining machines.

      Keywords: cutting process modeling, parts of ore-mining machines, quality indices, processing accuracy


  1. Derzhavna sluzhba statystyky Ukrainy. (2020). Retrieved from
  2. Prognoz mirovoy dinamiki potrebleniya uglya. (2019). Available at
  3. Utverzhdena Energostrategiya Ukrainy do 2035 goda. (2017). Retrieved from
  4. Karaguzel, U., Olgun, U., Uysal, E., Budak, E., & Bakkal, M. (2014). Increasing tool life in machining of difficult-to-cut materials using nonconventional turning processes. The International Journal of Advanced Manufacturing Technology, 77(9-12), 1993-2004.
  5. Parida, A.K., Rao, P.V., & Ghosh, S. (2019). Numerical analysis and experimental investigation in the machining of AISI 316 steel. Sādhanā, 45(1).
  6. El-Hossainy, T.M., El-Zoghby, A.A., Badr, M.A., Maalawi, K.Y., & Nasr, M.F. (2010). Cutting parameter optimization when machining different materials. Materials and Manufacturing Processes, 25(10), 1101-1114.
  7. Postnov, V.V., Khadiullin, S.Kh., Malakhov, E.N., & Starovoytov, S.V. (2012). Issledovanie pokazateley, opredelyayushchikh rezhushchie svoystva instrumental’nykh tverdykh splavov pri obrabotke trudnoobrabatyvaemykh materialov. Vestnik UGATU, 16(8(53)), 118-125.
  8. Philip Selvaraj, D., Chandramohan, P., & Mohanraj, M. (2014). Optimization of surface roughness, cutting force and tool wear of nitrogen alloyed duplex stainless steel in a dry turning process using Taguchi method. Measurement, (49), 205-215.
  9. Heisel, U., Kryvoruchko, D.V., Zaloha, V.A., Storchak, M., Emelyanenko, S.S., & Selivonenko, S.N. (2008). Finite element analysis of cutting force dynamics. Proceedings of the 11th CIRP International Workshop on Modeling of Machining Operations, 163-170.
  10. Heisel, U., Kryvoruchko, D.V., Zaloha, V.A., & Storchak, M. (2007). Cause analysis of errors in Fe prediction orthogonal cutting performances. Proceedings of the 10th CIRP International Workshop on Modeling of Machining Operations, 141-148.
  11. Dessoly, V., Melkote, S.N., & Lescalier, C. (2004). Modeling and verification of cutting tool temperatures in rotary tool turning of hardened steel. International Journal of Machine Tools and Manufacture, 44(14), 1463-1470.
  12. Ayupov, V.V. (2017). Matematicheskoe modelirovanie tekhnicheskikh system. Perm’, Rossiya: IPTs Prokrost’.
  13. Matalin, A.A. (1985). Tekhnologiya mashinostroeniya. Leningrad, Rossiya: Mashinostroenie.
  14. Kolev, K.S., & Gorchakov, L.M. (1976). Tochnost’ obrabotki i rezhimy rezaniya. Moskva, Rossiya: Mashinostroenie.
  15. Rezhimy rezaniya trudnoobrabatyvaemykh materialov. (1976). Moskva, Rossiya: Mashinostroenie.
  16. Vul’f, A.M. (1973). Rezanie metallov. Leningrad, Rossiya: Mashinostroenie.
  17. Arshinov, V.A., & Alekseev, G.A. (1967). Rezanie metallov i rezhushchiy instrument. Moskva, Rossiya: Mashinostroenie.
  18. Лицензия Creative Commons