This analysis reviews the advancements in digital twins for machine tools, indicating its potential for optimization and predictive maintenance.
The number of publications on digital twins went from 3.000 in 2017 to over 70.000 in 2024. This paper analyses the use and status of digital twins for machine tools as well as the necessary modelling and identification for enabling optimization, process planning, process control and predictive maintenance on the machine tool level and the fleet level. Recent research on digital twins for machine tools leveraging AI or greybox models is also presented. This paper gives an overview of the application and the technology behind digital twins used for machine tool design, commissioning, and operations.
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Verl et al. (2026) studied this question.
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