Application of Machine Learning in the Precise and Cost-Effective Self-Compensation of the Thermal Errors of CNC Machine Tools – A Review
1
Department of Machine Tools and Mechanical Technologies, Wroclaw University of Science and Technology, Poland
Submission date: 2022-06-14
Final revision date: 2022-07-08
Acceptance date: 2022-07-20
Online publication date: 2022-08-08
Corresponding author
Robert Czwartosz
Department of Machine Tools and Mechanical Technologies, Wroclaw University of Science and Technology, Wroclaw, Poland
Department of Machine Tools and Mechanical Technologies, Wroclaw University of Science and Technology, Wroclaw, Poland
Journal of Machine Engineering 2022;22(3):59-77
KEYWORDS
TOPICS
ABSTRACT
The current development of production engineering takes place through the innovative improvement of machine tools and machining processes at the constantly growing application of intelligent self-improvement functions. Machine learning opens up possibilities for machine tool self-improvement in real time. This paper discusses the state of knowledge relating to the application of machine learning for precise and cost-effective thermal error self-compensation. Data acquisition and processing, models and model learning and self-learning methods are also considered. Three highly effective error compensation systems (supported with machine learning) are analysed and conclusions and recommendations for future research are formulated.
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