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May 14, 2026Russian Engineering Research0 citations

Combined Numerical Geometric and Physical Modeling of CNC Machining

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ESE. I. Shchurova

Key Points

  • To enhance accuracy in CNC machining of thin-wall composite workpieces by addressing workpiece deformation and cutting force calculations.
  • Combined numerical geometric and physical modeling to analyze CNC machining processes.
  • Voxel and finite element modeling utilized for worn cutter and fiber-reinforced composite workpiece.
  • Calculation of cutter path adjusted for tool wear and cutting forces at specific machining points.
  • Successful modeling improved CNC machining accuracy for fiber-reinforced composites.
  • Cutting forces were accurately calculated at specific points on the work surface.
  • Modeling results allowed for adjustments to CNC control programs to optimize machining outcomes.

Abstract

Accuracy assurance of CNC machining of shaped thin-wall workpieces depends on numerous process factors, including workpiece deformation and tool wear. The problem is additionally complicated for fiber-reinforced composite workpieces due to the complexity of calculating cutting forces in their case. This creates the need for a comprehensive solution to such problems on a unified basis, which can currently be achieved through combined numerical geometric and physical modeling. The results of this modeling, as applied to milling, include calculation of the cutter path with adjustment for tool wear, voxel and finite element modeling of the worn cutter, including its surface roughness, modeling of a turbine blade workpiece made of a fiber-reinforced composite, and numerical calculation of the cutting force at a specific point on the work surface machined by the worn cutting wedge of the cutter. It is shown that the limitations of computing technology can be overcome by modeling these processes at selected points along the tool path. Modeling results can be subsequently used to adjust control programs for CNC machines.

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Cite This Study

E. I. Shchurova (2026) studied this question.

synapsesocial.com/papers/6a05661aa550a87e60a1e2bdhttps://doi.org/10.3103/s1068798x26700176
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