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<p>With the increasing adoption of carbon fiber-reinforced polyetheretherketone (CF/PEEK) composites and the growing demand for stringent surface and profile accuracy, milling of CF/PEEK is becoming increasingly important. Owing to the pronounced plasticity and thermal sensitivity of PEEK resin, milling readily induces damage, deformation, and severe tool wear. Controlling the milling force can effectively reduce machining-induced damage and tool wear; therefore, accurate prediction of milling force is essential for process optimization. However, because PEEK resin is highly sensitive to temperature variation and is prone to softening as the cutting temperature increases, the cutting-force behavior of CF/PEEK differs from that of conventional carbon fiber-reinforced epoxy (CF/epoxy). Accordingly, this study establishes an instantaneous macroscopic milling force prediction model for profile milling of CF/PEEK, considering the effect of cutting temperature. Based on the chip flow principle, the interaction between the helical cutting edges and the individual plies of the workpiece is quantified. Furthermore, given the pronounced thermal sensitivity of CF/PEEK, a regression formulation for the cutting force coefficients considering cutting temperature is established. Consequently, the milling force in ball-end milling of curved CF/PEEK components is predicted with an average error of 16.5%. The results show that increasing cutting temperature leads to a reduction in cutting force. Meanwhile, thermal softening of the PEEK matrix promotes surface resin smearing, thereby reducing the surface roughness of CF/PEEK. These findings support force prediction and process optimization in high-quality milling of CF/PEEK components.</p>

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A novel predictive modeling method in ball-end milling of CF/PEEK curved surfaces based on comprehensive multi-factor consideration

  • 期刊论文

  • 发表日期：

    2026年6月24日

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  • Xinman Yuan,
  • Fuji Wang,
  • Ge Song,
  • Pengcheng Ju,
  • Jun Deng,
  • Meng Zhao,
  • Wenchang Zhou

摘要

With the increasing adoption of carbon fiber-reinforced polyetheretherketone (CF/PEEK) composites and the growing demand for stringent surface and profile accuracy, milling of CF/PEEK is becoming increasingly important. Owing to the pronounced plasticity and thermal sensitivity of PEEK resin, milling readily induces damage, deformation, and severe tool wear. Controlling the milling force can effectively reduce machining-induced damage and tool wear; therefore, accurate prediction of milling force is essential for process optimization. However, because PEEK resin is highly sensitive to temperature variation and is prone to softening as the cutting temperature increases, the cutting-force behavior of CF/PEEK differs from that of conventional carbon fiber-reinforced epoxy (CF/epoxy). Accordingly, this study establishes an instantaneous macroscopic milling force prediction model for profile milling of CF/PEEK, considering the effect of cutting temperature. Based on the chip flow principle, the interaction between the helical cutting edges and the individual plies of the workpiece is quantified. Furthermore, given the pronounced thermal sensitivity of CF/PEEK, a regression formulation for the cutting force coefficients considering cutting temperature is established. Consequently, the milling force in ball-end milling of curved CF/PEEK components is predicted with an average error of 16.5%. The results show that increasing cutting temperature leads to a reduction in cutting force. Meanwhile, thermal softening of the PEEK matrix promotes surface resin smearing, thereby reducing the surface roughness of CF/PEEK. These findings support force prediction and process optimization in high-quality milling of CF/PEEK components.