OBRABOTKAMETALLOV Vol. 27 No. 2 2025 technology Conclusion 1. The dependences of the deviation from roundness and cylindricality on the feed per revolution have been established; as the feed increases, the values of deviation from roundness and cylindricality also increase. 2. It has been shown that during fine boring, despite the small allowance, the rigidity of the boring cutter significantly contributes to the accuracy of the resulting holes, accounting for about 20–30 % of the tolerance value. 3. An algorithm has been developed to determine the area of the cut layer for finishing boring operations, taking into account the geometric parameters of the cutting tool and the technological processing parameters, enabling the calculation of the cutting force. 4. A model of the radial displacement process of the boring cutter has been developed. This model incorporates data on the technological parameters of the hole finishing process and allows determination of the radial displacement value of the boring cutter used in error calculation. 5. Amethod for assigning transitions has been developed that accounts for the deviation of the hole axis during roughing stages, the influence of the allowance value based on the developed mathematical models, including preliminary adjustment of the boring cutter and correction for the tool radius. References 1. Östling D., Brede P.K., Jensen T., Bjønnum R., Standal O., Sæthertrø P.I., Holmström O.B.T. Real-time compensation of tool deflection using a sensor embedded boring bar with wireless signal feedback to the machine tool controller. 9th CIRP Conference on High Performance Cutting (HPC 2020), 2021, vol. 101, pp. 102–105. DOI: 10.1016/j.procir.2020.09.191. 2. Chernoivanova A.G., Tarasenko B.F., Os’kin S.V. Resursosberegayushchee ustroistvo dlya rastochki korpusnykh otverstii [Resource-saving device for boring hull holes]. Chrezvychainye situatsii: promyshlennaya i ekologicheskaya bezopasnost’ = Emergencies: industrial and environmental safety, 2015, no. 2–3, pp. 81–88. 3. Maslov A.R., Molodtsov V.V. Modelirovanie kolebanii instrumental’noi sistemy dlya rastachivaniya otverstii [Vibration simulation tooling system for boring]. Vestnik MGTU “Stankin” = Vestnik MSTU “Stankin”, 2014, no. 4, pp. 196–199. 4. Bakhno A.L. Yamnikov A.S., Vasilyev A.S., Chuprikov A.O. Povyshenie tochnosti rastachivaniya otverstii v svarnykh korpusakh [More precise reaming of holes in welded components]. STIN = Russian Engineering Research, 2019, no. 6, pp. 38–40. (In Russian). 5. Du W., Wang L., Shao Y. A semi-analytical dynamics method for spindle radial throw in boring process. Journal of Manufacturing Processes, 2023, vol. 96, pp. 110–124. DOI: 10.1016/j.jmapro.2023.04.047. 6. Stelmakov V.A., Gimadeev M.R., Iakuba D.D. Research on the process of forming cylindrical surfaces of holes during milling finish with end mills using a circular interpolation strategy. Proceedings of the 6th International Conference on Industrial Engineering (ICIE 2020). Vol. 2. Cham, Springer, 2021, pp. 917–925. DOI: 10.1007/9783-030-54817-9_106. 7. Cao H., Li B., Li Y., Kang T., Chen X. Model-based error motion prediction and fit clearance optimization for machine tool spindles. Mechanical Systems and Signal Processing, 2019, vol. 133, p. 106252. DOI: 10.1016/j. ymssp.2019.106252. 8. Chen Y., Zhao X., Gao W., Hu G., Zhang S., Zhang D. Anovel multi-probe method for separating spindle radial error from artifact roundness error. The International Journal of Advanced Manufacturing Technology, 2017, vol. 93, pp. 623–634. DOI: 10.1007/s00170-017-0533-5. 9. Gokulu T., Defant F., Albertelli P. Stability analysis of multi-insert rotating boring bar with stiffness variation. Journal of Sound and Vibration, 2024, vol. 586, p. 118497. DOI: 10.1016/j.jsv.2024.118497. 10. Liu T.I., Kumagai A., Wang Y.C., Song S.D., Fu Z., Lee J. On-line monitoring of boring tools for control of boring operations. Robotics and Computer-Integrated Manufacturing, 2010, vol. 26, pp. 230–239. DOI: 10.1016/j. rcim.2009.11.002. 11. Liu Z., Lang Z.Q., Gui Y., Zhu Y.P., Laalej H. Digital twin-based anomaly detection for real-time tool condition monitoring in machining. Journal of Manufacturing Systems, 2024, vol. 75, pp. 163–173. DOI: 10.1016/j. jmsy.2024.06.004.
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