Chatter model for enabling a digital twin in machining

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Publication date
2020-09
Author
Afazov, S.
Scrimieri, Daniele
Keyword
Digital twin
Chatter model
Cutting forces
Research Development Fund Publication Prize Award
Rights
© The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Abstract
This paper presents the development of a new chatter model using measured cutting forces instead of a mathematical model with empirical nature that describes them. The utilisation of measured cutting forces enables the prediction of real-time chatter conditions and stable machining. The chatter model is validated using fast Fourier transform (FFT) analyses for detection of chatter. The key contribution of the developed chatter model is that it can be incorporated in digital twins for process monitoring and control in order to achieve greater material removal rates and improved surface quality in future industrial applications involving machining processes.
URI
http://hdl.handle.net/10454/18176
Version
Published version
Citation
Afazov S and Scrimieri D (2020) Chatter model for enabling a digital twin in machining. The International Journal of Advanced Manufacturing Technology. 110: 2439-2444.
Link to publisher’s version
https://doi.org/10.1007/s00170-020-06028-9
Type
Article
Notes
Research Development Fund Publication Prize Award winner, Sep 2020.
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