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Machine tool calibration: Measurement, modeling, and compensation of machine tool errors

Published

Author(s)

Wei Gao, Soichi Ibaraki, Alkan Donmez, D. Kono, J.R.R Mayer, Yuan-Liu Chen, Karoly Szipka, Andreas Archenti, Jean-Marc Linares, N. Suzuki

Abstract

Advanced technologies for the calibration of machine tools are presented. Kinematic errors independently of their causes are classified into errors within one-axis as intra-axis errors, errors between axes as inter-axis errors, and as volumetric errors. As the major technological elements of machine tool calibration, the measurement methods, modeling theories, and compensation strategies of the machine tool errors are addressed. The criteria for selecting a combination of the technological elements for machine tool calibration from the point of view of accuracy, complexity, and cost are provided. Recent applications of artificial intelligence and machine learning in machine tool calibration are introduced. Remarks are also made on future trends in machine tool calibration.
Citation
International Journal of Machine Tools & Manufacture
Volume
187

Keywords

machine tool, calibration, error, kinematic, geometric, thermal, load, volumetric, uncertainty, error separation, machine learning, artificial intelligence

Citation

Gao, W. , Ibaraki, S. , Donmez, A. , Kono, D. , Mayer, J. , Chen, Y. , Szipka, K. , Archenti, A. , Linares, J. and Suzuki, N. (2023), Machine tool calibration: Measurement, modeling, and compensation of machine tool errors, International Journal of Machine Tools & Manufacture, [online], https://doi.org/10.1016/j.ijmachtools.2023.104017, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=935957 (Accessed June 20, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created April 20, 2023, Updated October 6, 2023