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- Title
Artificial intelligence enabled smart machining and machine tools.
- Authors
Chuo, Yu Sung; Lee, Ji Woong; Mun, Chang Hyeon; Noh, In Woong; Rezvani, Sina; Kim, Dong Chan; Lee, Jihyun; Lee, Sang Won; Park, Simon S.
- Abstract
Artificial intelligence (AI) in machine tools offers diverse advantages, including learning and optimizing machining processes, compensating errors, saving energy, and preventing failures. Various AI techniques have been proposed and applied; however, many challenges still exist that inhibit the use of AI for machining tasks. This paper deals with different types and usage of AI technologies in machining operations such as predictive modelling, parameter optimization and control, chatter stability, tool wear, and energy conservation. We discuss the challenges of AI technologies, such as data quality, transferability, explainability, and suggest future directions to overcome them.
- Subjects
ARTIFICIAL intelligence; COMPUTERS; MACHINE tools; MACHINE learning; ENERGY conservation; MACHINING; NUMERICAL control of machine tools
- Publication
Journal of Mechanical Science & Technology, 2022, Vol 36, Issue 1, p1
- ISSN
1738-494X
- Publication type
Article
- DOI
10.1007/s12206-021-1201-0