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<p>To provide researchers with a deeper understanding of and solutions to the prominent deformation control challenges in milling of large metal thin-walled components (LMTWC), this paper focuses on the milling of these components and systematically reviews recent research progress. First, it provides a detailed analysis of the key factors and intrinsic mechanisms that induce deformation in LMTWC during milling, including chatter, clamping force, cutting force/heat coupling, and residual stress, along with corresponding suppression strategies. The application and challenges of finite element analysis, machine learning, and on-machine measurement technologies for prediction and detection in LMTWC machining are then discussed. Building on this, the paper focuses on the need for efficient and precise machining, reviewing the principles, applications, and challenges of advanced deformation control strategies, including flexible clamping, adaptive machining, mirror milling, and ultrasonic assisted milling. This paper aims to provide systematic theoretical support and technical reference for deepening the understanding of deformation mechanisms in milling of LMTWC, developing high-precision deformation prediction and compensation technologies, and advancing the engineering application of advanced control strategies.</p>

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Research progress on deformation control in milling process of large metal thin-walled components

  • 期刊论文

  • 发表日期：

    2026年4月18日

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  • Quan Gao,
  • Rui Li,
  • Hanjun Gao,
  • Hechuan Song,
  • Shangru Yang,
  • Xuesi Hou,
  • Kai Yang,
  • Bin Zhang

摘要

To provide researchers with a deeper understanding of and solutions to the prominent deformation control challenges in milling of large metal thin-walled components (LMTWC), this paper focuses on the milling of these components and systematically reviews recent research progress. First, it provides a detailed analysis of the key factors and intrinsic mechanisms that induce deformation in LMTWC during milling, including chatter, clamping force, cutting force/heat coupling, and residual stress, along with corresponding suppression strategies. The application and challenges of finite element analysis, machine learning, and on-machine measurement technologies for prediction and detection in LMTWC machining are then discussed. Building on this, the paper focuses on the need for efficient and precise machining, reviewing the principles, applications, and challenges of advanced deformation control strategies, including flexible clamping, adaptive machining, mirror milling, and ultrasonic assisted milling. This paper aims to provide systematic theoretical support and technical reference for deepening the understanding of deformation mechanisms in milling of LMTWC, developing high-precision deformation prediction and compensation technologies, and advancing the engineering application of advanced control strategies.