PREDICTION OF CUTTING PROCESS STABILITY: A REVIEW OF PUBLICATIONS
DOI:
https://doi.org/10.36910/4293-52779-2025-17-01-07Keywords:
Intelligent control systems, spindle unit, stability lobe diagram, chatter, machine learning, vibration prediction.Abstract
This article reviews modern methods for predicting the stability of metal cutting processes, a crucial aspect for ensuring the quality and efficiency of machining in mechanical engineering. The authors conduct a systematic analysis of scientific publications dedicated to the construction of Stability Lobe Diagrams (SLD), which define optimal cutting regimes to avoid chatter. The paper considers both theoretical approaches to SLD construction, based on the mathematical modeling of cutting dynamics and the solution of delay differential equations, and experimental methods that utilize data obtained directly during machining. Frequency domain methods, discrete methods, and numerical methods are analyzed, along with experimental approaches such as machine learning based on acoustic signals and the step-by-step increase of cutting depth method. Particular attention is paid to the application of SLD for predicting stability when machining flexible workpieces, where the dynamic interaction between the tool and the workpiece is critically important. A comparative analysis of different SLD construction methods is carried out, identifying their advantages and disadvantages, as well as their areas of application. Based on the review, conclusions are drawn about the relevance of further research in the direction of improving the methods of constructing and practically applying SLDs for optimizing cutting regimes, increasing productivity, and enhancing the quality of machining on various types of machine tools.
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