OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 7 No. 1 2025 Fig. 24. Dependence of the surface quality obtained during cutting on the cutting tool wear It should be noted that both the model and experimental characteristics show stabilization and even some decrease in the Ra value in the stabilization area of the cutting tool wear curve (see Fig. 24). The digital twin technology relies on the widespread use of virtual mathematical models, the numerical simulation of which can predict the development of various processes in technical systems. The importance of such a prediction largely depends on the accuracy of the models used in the simulation, which in turn require constant parametric adjustment of the parameters. Primarily, such adjustment is associated with the increasing wear of the cutting tool, which must also be modeled in the digital twin system. The particular cutting case that we have considered only allows us to conclude the possibility of predicting the surface quality obtained during cutting based on calculations performed on virtual models of the digital twin. Overall, the purpose of the study set at the beginning of the paper has been achieved, mainly due to the introduction of a module for calculating the increase in cutting tool wear into the model, and also due to the parametric identification of the remaining model parameters. Studies have shown that the accuracy of predicting the dependence of the surface quality obtained during cutting on the cutting tool wear is sufficiently high for this particular case. The largest discrepancies between the modeled and experimental characteristics are observed in the range from 0.25 mm to 0.36 mm of cutting tool wear. This range is characterized by the largest deviation of the experimental and simulated curves of cutting tool wear (see Figs. 8 and 19). In the example we provided, the cutting tool wear curve along the cutting path behaved classically, and three wear areas could be identified on it, as well as on the simulated characteristic. However, this is a specific case, and the cutting tool wear may increase abruptly, in a jump, due to various random factors. For this case, it is necessary to integrate an intelligent subsystem for recognizing such non-standard cases of cutting tool wear development into the parameter identification system of the virtual models of digital twins. Conclusion This work considered the issues of assessing the interrelationship between cutting tool wear and the quality of the surfaces obtained during cutting. The quality of the surfaces obtained during cutting was assessed using the Ra value, which proved to be the most informative for the case under consideration, both for processing experimental data and for simulating. Given the dependencies obtained in Fig. 24, it can be asserted that predicting the quality of the surface of parts obtained by cutting based on the results
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