What question did this study set out to answer?

The aim is to explore intelligent maintenance systems for machine tools using digital twins and machine learning.

January 22, 2026Applied SciencesOpen Access

Multiparametric Vibration Diagnostics of Machine Tools Within a Digital Twin Framework Using Machine Learning

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The aim is to explore intelligent maintenance systems for machine tools using digital twins and machine learning.
Reviewed international standards and existing vibration diagnostic technologies.
Developed a predictive maintenance system with a digital twin architecture.
Utilized machine learning methods including Long Short-Term Memory networks and Multilayer Perceptron models for analysis.
Conducted laboratory testing on a turning machining center.
Demonstrated the system's capability for assessing technical conditions based on multiparametric data.
Showed promise in short-term vibration trend forecasting.
Achieved effective state classification of machine tools using a multilayer neural network.

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Implication

A review reveals the effectiveness of machine learning in improving diagnostic systems for machine tools, suggesting enhanced maintenance capabilities.

Cite This Study

Kurkin et al. (2026) studied this question.

synapsesocial.com/papers/6971bd90642b1836717e22a8 https://doi.org/10.3390/app16020982

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Implication

A review reveals the effectiveness of machine learning in improving diagnostic systems for machine tools, suggesting enhanced maintenance capabilities.

Multiparametric Vibration Diagnostics of Machine Tools Within a Digital Twin Framework Using Machine Learning

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Discussion

Implication

Cite This Study

Multiparametric Vibration Diagnostics of Machine Tools Within a Digital Twin Framework Using Machine Learning

Key Points

Discussion

Implication

Cite This Study

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