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<p>In-situ prediction and intelligent monitoring of micro-milling tool wear remain challenging in micro-milling technology. Digital twin technology provides a promising solution for addressing these challenges. This study proposed a digital twin-based monitoring system for micro-milling tool wear. First, micro-milling tool wear experiments were conducted, using the tool diameter reduction rate and flank wear land width as evaluation indicators. An intelligent prediction model based on a Long Short-Term Memory (LSTM) network was developed to achieve high-precision forecasts of tool wear. Subsequently, the overall architecture of the digital twin-based monitoring system was designed. A micro-milling motion simulation model was established to enable real-time data acquisition, preprocessing, and transmission of micro-milling force data. Leveraging the Unity 3D software development platform and C# programming language, a digital twin-based micro-milling tool wear monitoring system was developed. This system enables twin reproduction of the micro-milling process and tool wear monitoring, providing essential support for intuitive visualization of the micro-milling process and accurate assessment of tool wear status.</p>

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Digital twin-based tool wear monitoring of micro-milling process

  • 期刊论文

  • 发表日期：

    2026年1月16日

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  • Ziming Wang,
  • Zhiyi Zhang,
  • Yuchen Zhao,
  • Zhonghao Zhu,
  • Fanmao Zeng,
  • Xiaohong Lu

摘要

In-situ prediction and intelligent monitoring of micro-milling tool wear remain challenging in micro-milling technology. Digital twin technology provides a promising solution for addressing these challenges. This study proposed a digital twin-based monitoring system for micro-milling tool wear. First, micro-milling tool wear experiments were conducted, using the tool diameter reduction rate and flank wear land width as evaluation indicators. An intelligent prediction model based on a Long Short-Term Memory (LSTM) network was developed to achieve high-precision forecasts of tool wear. Subsequently, the overall architecture of the digital twin-based monitoring system was designed. A micro-milling motion simulation model was established to enable real-time data acquisition, preprocessing, and transmission of micro-milling force data. Leveraging the Unity 3D software development platform and C# programming language, a digital twin-based micro-milling tool wear monitoring system was developed. This system enables twin reproduction of the micro-milling process and tool wear monitoring, providing essential support for intuitive visualization of the micro-milling process and accurate assessment of tool wear status.