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In-Process Identification of the Cutting Force Coefficients in Milling based on a Virtual Machining Model

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Abstract

The in-process monitoring of cutting force coefficients can provide information with which to determine tool wear and tool deflection during machining processes. The robustness of monitoring and control algorithms utilizing virtual machining can also be improved with well-identified cutting coefficients. However, conventional methods for calibrating the coefficients require sets of measured forces in various cutting conditions for linear regression analysis. In this study, we propose to identify the cutting force coefficients using an optimization method to acquire the coefficients from a single cutting condition. The optimization method modifies the design parameters (i.e., arbitrary cutting coefficients) to reduce the discrepancy between the measured and simulated cutting forces, and determines the optimal design parameters (i.e., identifies the cutting coefficients). The proposed method predicts cutting forces more accurately compared to the conventional method. For the real-time identification of the cutting coefficients during the operation, a virtual machining model is utilized, and accurate and rapid calculations are achieved. Moreover, the behaviors of the identified cutting coefficients related to the tool geometry, feed direction, and radial immersion are examined. The proposed method is implemented at a CNC machining center and is experimentally validated.

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Acknowledgements

This study has been conducted with the support of the Korea Institute of Industrial Technology as "Development of Core Technologies for a Working Partner Robot in the Manufacturing Field (KITECH EO-22-0009)”.

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Authors and Affiliations

  1. Digital Transformation R&D Department, Korea Institute of Industrial Technology, 143 Hanggaulro, Sangrok-gu, Ansan-si, Gyeonggi-do, 15588, Republic of Korea

    Guseon Kang, Jaehyeok Kim, Youngjae Choi & Dong Yoon Lee

  2. Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea

    Guseon Kang

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  1. Guseon Kang
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  2. Jaehyeok Kim
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Correspondence to Dong Yoon Lee.

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Kang, G., Kim, J., Choi, Y. et al. In-Process Identification of the Cutting Force Coefficients in Milling based on a Virtual Machining Model. Int. J. Precis. Eng. Manuf. 23, 839–851 (2022). https://doi.org/10.1007/s12541-022-00677-4

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  • DOI: https://doi.org/10.1007/s12541-022-00677-4

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