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2000
Volume 3, Issue 1
  • ISSN: 2950-3752
  • E-ISSN: 2950-3760

Abstract

In recent years, the rapid advancement of digital technology has driven the manufacturing industry towards greater digitalization, networking, and intelligence. Digital twin technology has emerged as a key enabler in the CNC machine tool life prediction field, focusing on establishing accurate life prediction models. By integrating virtual models with comprehensive data, digital twins support fault diagnosis, enhance prediction accuracy, and improve reliability. This paper explores digital twin-driven CNC machine tools, beginning with an introduction to their conceptual framework and modelling methods. It then delves into the specific applications of digital twins across the product lifecycle, highlighting mainstream life prediction methods for core components, particularly cutting tools. Additionally, the paper analyzes workpiece-related factors in thermal error modelling and examines the prospects of digital twins in CNC machine tool life prediction. Future research should prioritize real-time multi-source data integration, adaptive prediction models for varying conditions, and AI-driven optimization to enhance the accuracy and applicability of digital twin technology in manufacturing.

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2025-05-07
2026-03-08

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Recent Patents on Digital Twin Technology Predict the Life of Machine Tool Components
Curr Arti Intell 3, E29503752358434 (2025); https://doi.org/10.2174/0129503752358434250410044244
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  • Article Type:     Review Article
Keyword(s): CNC machine tool; Digital twin; electrical spindle; intellectualize; life prediction; thermal error

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