OBRABOTKAMETALLOV Vol. 27 No. 1 2025 127 EQUIPMENT. INSTRUMENTS References 1. Suslov A.G. Kachestvo poverkhnostnogo sloya detalei mashin [The quality of the surface layer of machine parts]. Moscow, Mashinostroenie Publ., 2000, 320 p. ISBN 5-217-02976-5. 2. Gimadeev M.P., Li A.A. Analiz avtomatizirovannykh sistem opredeleniya parametrov sherokhovatosti poverkhnosti na osnove dinamicheskogo monitoringa [Analysis of automated surface roughness parameter support systems based on dynamic monitoring]. Advanced Engineering Research, 2022, no. 2 (22), pp. 116–129. DOI: 10.23947/2687-1653-2022-22-2-116-129. 3. Tugengol’d A.K., Luk’yanov E.A., Voloshin R.N., Bonilla V.F. Intellektual’naya sistema monitoringa i upravleniya tekhnicheskim sostoyaniem mekhatronnykh tekhnologicheskikh ob”ektov [Intelligent system for monitoring and controlling the technical condition of mechatronic process facilities]. Vestnik Donskogo Predicting machined surface quality under conditions of increasing tool wear Victor Lapshin a, *, Alexandra Gubanova b, Ilya Dudinov c Don State Technical University, 1 Gagarin square, Rostov-on-Don, 344000, Russian Federation a https://orcid.org/0000-0002-5114-0316, lapshin1917@yandex.ru; b https://orcid.org/0000-0002-9785-5384, anatoliya81@mail.ru; c https://orcid.org/0009-0009-0784-1287, ilya.sandman@yandex.ru Obrabotka metallov - Metal Working and Material Science Journal homepage: http://journals.nstu.ru/obrabotka_metallov Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science. 2025 vol. 27 no. 1 pp. 106–128 ISSN: 1994-6309 (print) / 2541-819X (online) DOI: 10.17212/1994-6309-2025-27.1-106-128 ART I CLE I NFO Article history: Received: 29 November 2024 Revised: 19 December 2024 Accepted: 23 January 2025 Available online: 15 March 2025 Keywords: Wear Vibrations Cutting process Surface quality Funding The study was carried out with the fi nancial support of the RSF grant No. 24-29-00287. ABSTRACT Introduction. The most important factor determining the effi ciency of metal cutting is the quality of the surface of the part obtained during cutting. The surface quality of a machined part is directly dependent on the vibration activity of the cutting tool, the amplitude of which is infl uenced by the complex evolutionary dynamics of the cutting process. In light of this, modern digital twin technology, which allows predicting the surface quality values of the parts using virtual models, is becoming an extremely relevant way to improve the effi ciency in metalworking control systems. The purpose of the work. This study aims to improve the prediction accuracy of a digital twin system for the surface quality of the machined parts under conditions of increasing cutting tool wear. The paper examines: the dynamics of the turning process of metal parts, as well as a mathematical model describing the dynamics of tool vibrations during metal machining on lathes, considering the infl uence of the thermodynamic subsystem of the cutting system. Research methods. An experimental approach was employed, utilizing a author-designed measuring stand along with a modern inverted metallographic microscope LaboMet-I version 4, equipped with wide-angle lenses 5/20, having a 20 mm linear fi eld of view, and a digital camera for microscopes Ucam-1400 with a 1.4 μm×1.4 μm matrix, and a contour profi le recorder T4HD. Furthermore, the study used mathematical modeling of the dynamic cutting system in the Matlab environment, for which the authors developed a specialized data processing program. Results and discussion. Curves depicting the tool wear rate, changes in the quality parameters of the machined surface as functions of cutting path, and as a function of cutting tool wear are constructed. Dynamic indicators suitable for parametric identifi cation of virtual digital twin models are determined. The structure of these models is established, and parametric identifi cation is performed. Numerical modeling is conducted in the Matlab environment, based on the results of which a curve depicting the change in average arithmetic surface roughness as a function of increasing tool wear is constructed. The convergence of the results of fi eld and numerical experiments is evaluated, which shows a high reliability of the surface quality prediction achievable through the use of digital twin systems. For citation: Lapshin V.P., Gubanova A.A., Dudinov I.O. Predicting machined surface quality under conditions of increasing tool wear. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science, 2025, vol. 27, no. 1, pp. 106–128. DOI: 10.17212/1994-6309-2025-27.1-106-128. (In Russian). ______ * Corresponding author Lapshin Viktor P., Ph.D. (Engineering), Associate Professor Don State Technical University, 1 Gagarin square, 344000, Rostov-on-don, Russian Federation Tel.: +7 900 122-75-14, e-mail: lapshin1917@yandex.ru
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