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Artificial intelligence enabled smart machining and machine tools

Alternative Title
Artificial intelligence enabled smart machining and machine tools
Author(s)
Chuo, Yu SungLee, Ji WoongMun, Chang HyeonNoh, In WoongRezvani, SinaKim, Dong ChanLee, JihyunLee, Sang WonPark, Simon S.
Issued Date
2022-01
DOI
10.1007/s12206-021-1201-0
URI
https://scholarworks.unist.ac.kr/handle/201301/62060
Citation
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, v.36, no.1, pp.1 - 23
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.
Publisher
대한기계학회
ISSN
1738-494X
Keyword (Author)
Artificial intelligenceIndustry 4.0Machine learningMachine toolsMachining

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