Obrabotka Metallov 2024 Vol. 26 No. 1

OBRABOTKAMETALLOV Vol. 26 No. 1 2024 174 MATERIAL SCIENCE 22. Rajput R.K. A textbook of fl uid mechanics and hydraulic machines. New Delhi, S. Chand, 2004. ISBN 9789385401374. 23. Saravanakumar A., Karthikeyan S.C., Dhamotharan B., Gokul kumar V. Optimization of CNC turning parameters on aluminum alloy 6063 using Taguchi Robust Design. Materials Today: Proceedings, 2018, vol. 5 (2), pp. 8290–8298. DOI: 10.1016/j.matpr.2017.11.520. 24. Smith W.F. Structure and properties of engineering alloys. New York, McGraw-Hill, 1981. 512 p. ISBN 0070585601. ISBN 978-0070585607. 25. Zou B., Chen M., Li S. Study on fi nish-turning of NiCr20TiAl nickel-based alloy using Al2O3/TiN-coated carbide tools. The International Journal of Advanced Manufacturing Technology, 2011, vol. 53 (1), pp. 81–92. DOI: 10.1007/s00170-010-2823-z. 26. Dessoly V., Melkote S.N., Lescalier C. Modeling and verifi cation of cutting tool temperatures in rotary tool turning of hardened steel. International Journal of Machine Tools and Manufacture, 2004, vol. 44 (14), pp. 1463– 1470. DOI: 10.1016/j.ijmachtools.2004.05.007. 27. Rezende B.A., Magalhaes F.C., Rubio J.C.C. Study of the measurement and mathematical modelling of temperature in turning by means equivalent thermal conductivity. Measurement, 2020, vol. 152, pp. 107275. DOI: 10.1016/j.measurement.2019.107275. 28. Kitagawa T., Kubo A., Maekawa K. Temperature and wear of cutting tools in high-speed machining of Inconel 718 and Ti–6Al–6V–2Sn. Wear, 1997, vol. 202 (2), pp. 142–148. DOI: 10.1016/S0043-1648(96)07255-9. 29. Pawade R.S., Joshi S.S. Analysis of acoustic emission signals and surface integrity in the high-speed turning of Inconel 718. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2012, vol. 226 (1), pp. 3–27. DOI: 10.1177/0954405411407656. 30. Aydın M., Karakuzu C., Uçar M., Cengiz A., Çavuşlu M.A. Prediction of surface roughness and cutting zone temperature in dry turning processes of AISI304 stainless steel using ANFIS with PSO learning. The International Journal of Advanced Manufacturing Technology, 2013, vol. 67 (1), pp. 957–967. DOI: 10.1007/s00170-012-4540-2. Confl icts of Interest The authors declare no confl ict of interest. © 2024 The Authors. Published by Novosibirsk State Technical University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0).

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