Predictive digital twin-driven dynamic error control for slow-tool-servo ultraprecision diamond turning

Xichun Luo; Qi Liu; Abhilash Puthanveettil Madathil; Wenkun Xie

doi:10.1016/j.cirp.2024.04.080

Predictive digital twin-driven dynamic error control for slow-tool-servo ultraprecision diamond turning

Xichun Luo, Qi Liu, Abhilash Puthanveettil Madathil, Wenkun Xie

Department of Mechanical Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

A predictive digital twin (DT)-driven dynamic error control approach is presented for accuracy control in high-frequency slow-tool-servo ultraprecision diamond turning processes. An explainable artificial intelligence-enabled real-time DT of the total dynamic error (inside and outside the servo loop) was established using in-line acceleration input data near the tool. A feedforward controller was used to mitigate the total dynamic errors before they came into effect. The machining trials using this approach showed that significant improvement in machining accuracy (87%, surface form accuracy; 95%, phase accuracy with precisions of 0.06 µm and 0.05°), and efficiency (8 times the state-of-the-art) were successfully achieved.

Original language	English
Pages (from-to)	377-380
Number of pages	4
Journal	CIRP Annals
Volume	73
Issue number	1
Early online date	18 May 2024
DOIs	https://doi.org/10.1016/j.cirp.2024.04.080
Publication status	Published - 22 Jul 2024

Funding

The authors would like to thank EPSRC (EP/K018345/1, EP/T024844/1, EP/V055208/1), Dr. Simon Smith and Dr. Chris Charlesworth of Aerotech Ltd for supporting this research.

Funders	Funder number
Engineering and Physical Sciences Research Council	EP/V055208/1, EP/K018345/1, EP/T024844/1
Engineering and Physical Sciences Research Council

Keywords

Accuracy
Digital twin
Dynamic error control

ASJC Scopus subject areas

Mechanical Engineering
Industrial and Manufacturing Engineering

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10.1016/j.cirp.2024.04.080Licence: CC BY

Cite this

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AB - A predictive digital twin (DT)-driven dynamic error control approach is presented for accuracy control in high-frequency slow-tool-servo ultraprecision diamond turning processes. An explainable artificial intelligence-enabled real-time DT of the total dynamic error (inside and outside the servo loop) was established using in-line acceleration input data near the tool. A feedforward controller was used to mitigate the total dynamic errors before they came into effect. The machining trials using this approach showed that significant improvement in machining accuracy (87%, surface form accuracy; 95%, phase accuracy with precisions of 0.06 µm and 0.05°), and efficiency (8 times the state-of-the-art) were successfully achieved.

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Predictive digital twin-driven dynamic error control for slow-tool-servo ultraprecision diamond turning

Abstract

Funding

Keywords

ASJC Scopus subject areas

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