OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 7 5 12. Erkorkmaz K., Altintas Y., Yeung C.-H. Virtual computer numerical control system. CIRP Annals, 2006, vol. 55 (1), pp. 399–402. DOI: 10.1016/S0007-8506(07)60444-2. 13. Kilic Z.M., Altintas Y. Generalized mechanics and dynamics of metal cutting operations for unified simulations. International Journal of Machine Tools and Manufacture, 2016, vol. 104, pp. 1–13. DOI: 10.1016/j. ijmachtools.2016.01.006. 14. Estman L., Merdol D., Brask K.-G., Kalhori V., Altintas Y. Development of machining strategies for aerospace components, using virtual machining tools. New Production Technologies in Aerospace Industry. Cham, Springer, 2014, pp. 63–68. DOI: 10.1007/978-3-319-01964-2_9. 15. Kozochkin M.P., Sabirov F.S., Seleznev A.E. Vibroakusticheskii monitoring lezviinoi obrabotki zagotovok iz zakalennoi stali [Vibroacoustic monitoring of cutting edge machining of hardened steel]. Vestnik MGTU «Stankin» = Vestnik MSUT “Stankin”, 2018, no. 1 (44), pp. 23–30. 16. Barzov A.A., Gorelov V.A., Igonkin B.A. Akustoelektricheskaya diagnostika protsessa rezaniya polimernykh kompozitsionnykh materialov [Acoustoelectric diagnostics of the cutting process of polymer composite materials]. Aviatsionnaya promyshlennost’ = Aviation Industry, 1986, no. 12, p. 36. 17. Altintas Y., Kersting P., Biermann D., Budak E., Denkena B. Virtual process systems for part machining operations. CIRP Annals, 2014, vol. 63 (2), pp. 585–605. DOI: 10.1016/j.cirp.2014.05.007. 18. Altintas Y., Brecher C., Weck M., Witt S. Virtual machine tool. CIRP Annals, 2005, vol. 54 (2), pp. 115–138. DOI: 10.1016/S0007-8506(07)60022-5. 19. Soori M., Arezoo B., Habibi M. Virtual machining considering dimensional, geometrical and tool deflection errors in three-axis CNC milling machines. Journal of Manufacturing Systems, 2014, vol. 33 (4), pp. 498–507. DOI: 10.1016/j.jmsy.2014.04.007. 20. Tieng H., Yang H.C., Hung M.H., Cheng F.T. A novel virtual metrology scheme for predicting machining precision of machine tools. IEEE International Conference on Robotics and Automation. IEEE, 2013, pp. 264–269. DOI: 10.1109/ICRA.2013.6630586. 21. Astakhov V.P. Geometry of single-point turning tools and drills: Fundamentals and practical applications. London, Springer, 2010. 566 p. DOI: 10.1007/978-1-84996-053-3. 22. Konrad H., Isermann R., Oette H.U. Supervision of tool wear and surface quality during endmilling operations. IFAC Proceedings Volumes, 1994, vol. 27 (4), pp. 507–513. DOI: 10.1016/S1474-6670(17)46074-5. 23. Zakovorotny V.L., Bordachev E.V. Informatsionnoe obespechenie sistemy dinamicheskoi diagnostiki iznosa rezhushchego instrumenta na primere tokarnoi obrabotki [Information support for the system of dynamic diagnostics of cutting tool wear using the example of turning]. Problemy mashinostroeniya i nadezhnosti mashin = Journal of Machinery Manufacture and Reliability, 1995, no. 3, pp. 95–103. 24. Grigoriev A.S. Instrumentarii sistemy ChPU dlya diagnostiki i prognozirovaniya iznosa rezhushchego instrumenta v real’nom vremeni pri tokarnoi obrabotke [CNC tool for diagnostic and prediction of cutting tool wear in real time for turning processing]. Vestnik MGTU «Stankin» = Vestnik MSUT “Stankin”, 2012, no. 1 (18), pp. 39–43. 25. Zakovorotny V.L., Gvindjiliya V.E. Evolyutsiya dinamicheskoi sistemy rezaniya, obuslovlennaya neobratimymi preobrazovaniyami energii v zone obrabotki [Evolution of the dynamic cutting system caused by irreversible energy transformations in the processing zone]. STIN = Russian Engineering Research, 2018, no. 12, pp. 17–25. (In Russian). 26. Zakovorotny V.L., Gvindjiliya V.E. Svyaz’ samoorganizatsii dinamicheskoi sistemy rezaniya s iznashivaniem instrumenta [Link between the self-organization of dynamic cutting system and tool wear]. Izvestiya vuzov. Prikladnaya nelineinaya dinamika = Izvestiya VUZ. Applied Nonlinear Dynamics, 2020, vol. 28, no. 1, pp. 46–61. DOI: 10.18500/0869-6632-2020-28-1-46-61. 27. ZakovorotnyV.L., GvindjiliyaV.E., KislovK.V. Information properties of frequency characteristics of dynamic cutting systems in the diagnosis of tool wear. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science, 2024, vol. 26, no. 3, pp. 114–134. DOI: 10.17212/1994-6309-2024-26.3-114-134. 28. Rizal M., Ghani J.A., Nuawi M.Z., Haron C.H. A review of sensor system and application in milling process for tool condition monitoring. Research Journal of Applied Sciences, Engineering and Technology, 2014, vol. 7 (10), pp. 2083–2097. DOI: 10.19026/rjaset.7.502. 29. Teti R. Advanced IT methods of signal processing and decision making for zero defect manufacturing in machining. Procedia CIRP, 2015, vol. 28, pp. 3–15. DOI: 10.1016/ j.procir.2015.04.003.
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