OBRABOTKAMETALLOV technology Vol. 27 No. 2 2025 The most frequently used machining methods for high-precision holes in finishing operations are reaming and boring. The boring operation is widely used in modern mechanical engineering. Boring tools can be multi-blade or single-blade. Multi-blade tools are most often used for rough machining of holes, while single-blade boring tools are applied in finishing and fine boring operations. Boring tools are adjusted to the size being performed, which is their main advantage. However, in practice, the boring operation is highly labor-intensive due to the need for adjustment to the required size [1–4]. It is necessary to use multi-pass processing with preliminary adjustment of the cutter, subsequent measurement, and repeated passes. This issue is minimized by automated systems for adjusting the boring head to the processing size within the machining center using measuring systems. The boring method allows achieving high precision parameters in terms of diametrical size as well as axis location [1, 5], in comparison to tools such as reamers, countersinks, and holes obtained using the milling method [6]. This is directly related to the cutting forces arising during processing, which are significantly lower with the finish boring method. However, the authors in [5] note the presence of elastic deformations (radial displacement of the boring cutter) and highlight the importance of this factor when boring deep holes. The paper proposes usng a semi-analytical dynamic method to determine the magnitude of elastic deformations of a boring tool. In the works of the authors [7–9], various approaches to dynamic systems describing elastic deformations of boring tools during processing are investigated. Also, in [1], to eliminate elastic deformations of the boring tool during machining, the use of built-in strain gauges in the boring tool was investigated. According to the study, these sensors measure the bending of the boring cutter in real time. Strain data is transmitted to the CNC system of the machine through a programmable logic controller. Based on this data, the system automatically compensates for bending by adding a corrective offset along the coordinate axes of the machine. The authors also note that the developed system allows for a significant reduction in the error of the diameter size of the hole, especially at small cutting depths. Some authors [10] consider an online monitoring system [11] for boring operations. They propose a methodology for effective online monitoring of tool conditions, which includes the use of adaptive neurofuzzy inference systems (ANFIS) for measuring the degree of wear and artificial neural networks (BPN — back propagation neural network) for classifying tool condition. This approach allows the boring process to be stopped timely when the wear threshold is reached, ensuring accuracy and preventing defects. The operation of artificial neural networks and neuro-fuzzy inference systems is based on the registration of cutting force signals (tangential, longitudinal, and radial) obtained from piezoelectric dynamometers. Some research teams are working on developing and optimizing the designs of boring tools. For instance, the authors [12] proposed a new device for ultrasonic elliptical vibration boring. The research results showed that this device effectively reduces vibrations during processing and helps improve the quality of the machined surface. The authors [13] investigated the vibration stability of the boring process using dynamic vibration absorbers (DVA). The study demonstrated that using dynamic vibration absorbers with optimal damping and rigidity parameters significantly reduces the vibration amplitude of the boring cutter. The main accuracy parameter achieved in the considered works was the diametrical size of the obtained holes. These works also addressed issues related to ensuring the form accuracy (deviations from roundness and cylindricity). Currently, measurement of hole form deviations is performed in accordance with international standards regulating the main evaluation methods — ISO 12181–1:2011 and ISO 4291:1985, namely [14, 15]: Least squares circle (LSC); Minimum circumscribed circle (MCC); Maximum inscribed circle (MIC); Minimum zone circle (MZC). The authors [18] described mathematical models for each of these methods and conducted experiments to evaluate their effectiveness. Based on the results, they proposed an improved assessment algorithm that reduces measurement error when using the MZC method.
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