Enhancement of Machining Accuracy Based on Prediction of Tool Deflection Considering Feedrate Change of Machine Tools

High-speed and high-accuracy machining have become indispensable requirements in modern manufacturing, particularly with the widespread use of computer numerical control (CNC) machine tools in precision engineering applications. However, one of the key challenges in achieving high machining accuracy is the deviation between the programmed feedrate and the actual feedrate during operation, caused by the acceleration and deceleration (Acc/Dec) behavior of the machine tool's servo control system. These discrepancies lead to deviations in the toolpath, which in turn reduce the dimensional accuracy and surface quality of the machined components. Compounding this issue, the cutting forces acting on the tool during high-speed milling operations—especially with square-end mills—cause elastic deflection of the tool, further compromising the geometric precision of the final product. To address these challenges, this study proposes an integrated methodology that combines modeling of actual feedrate variation with predictive estimation of cutting force and tool deflection. The feedrate model is developed by considering the Acc/Dec characteristics of the control axes in the machine tool, enabling accurate prediction of real tool movements. Simultaneously, a cutting force model is constructed based on machining parameters and tool geometry to estimate the magnitude of tool deflection. By integrating both models, the proposed approach allows for the accurate prediction of the actual toolpath and compensation for deviations arising from control limitations and mechanical deflection. The effectiveness of this method was validated through machining experiments conducted without high-precision contour control. The results demonstrated a strong correlation between predicted and measured toolpaths, confirming the reliability and practicality of the proposed method. This study highlights the importance of accounting for dynamic feedrate behavior and cutting mechanics in improving machining accuracy, offering a valuable solution for enhancing dimensional control in high-speed CNC milling applications.

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Publication Details

Journal
Science & Technology Development Journal - Engineering and Technology
Published
2025-01-01
DOI
https://doi.org/10.32508/stdjet.v6isi2.1106
Primary Topic
Advanced Measurement and Metrology Techniques
Type
article
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article

Enhancement of Machining Accuracy Based on Prediction of Tool Deflection Considering Feedrate Change of Machine Tools

Thien Phuc Tran, Trong Khanh Dat Than
Science & Technology Development Journal - Engineering and Technology
Advanced Measurement and Metrology Techniques
article

Enhancement of Machining Accuracy Based on Prediction of Tool Deflection Considering Feedrate Change of Machine Tools

Thien Phuc Tran, Trong Khanh Dat Than
article en

Abstract

High-speed and high-accuracy machining have become indispensable requirements in modern manufacturing, particularly with the widespread use of computer numerical control (CNC) machine tools in precision engineering applications. However, one of the key challenges in achieving high machining accuracy is the deviation between the programmed feedrate and the actual feedrate during operation, caused by the acceleration and deceleration (Acc/Dec) behavior of the machine tool's servo control system. These discrepancies lead to deviations in the toolpath, which in turn reduce the dimensional accuracy and surface quality of the machined components. Compounding this issue, the cutting forces acting on the tool during high-speed milling operations—especially with square-end mills—cause elastic deflection of the tool, further compromising the geometric precision of the final product. To address these challenges, this study proposes an integrated methodology that combines modeling of actual feedrate variation with predictive estimation of cutting force and tool deflection. The feedrate model is developed by considering the Acc/Dec characteristics of the control axes in the machine tool, enabling accurate prediction of real tool movements. Simultaneously, a cutting force model is constructed based on machining parameters and tool geometry to estimate the magnitude of tool deflection. By integrating both models, the proposed approach allows for the accurate prediction of the actual toolpath and compensation for deviations arising from control limitations and mechanical deflection. The effectiveness of this method was validated through machining experiments conducted without high-precision contour control. The results demonstrated a strong correlation between predicted and measured toolpaths, confirming the reliability and practicality of the proposed method. This study highlights the importance of accounting for dynamic feedrate behavior and cutting mechanics in improving machining accuracy, offering a valuable solution for enhancing dimensional control in high-speed CNC milling applications.

Science & Technology Development Journal - Engineering and Technology
Vietnam National University Ho Chi Minh City (VN), Ho Chi Minh City University of Technology (VN)
Openalex Percentile: Top 86%
Advanced Measurement and Metrology Techniques
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