Direct Surface-Based Meshing and Measurement-Driven Cutter Edge Reconstruction for Cylindrical Gear Skiving

Most existing analytical models for gear skiving define the cutting edge indirectly through hypothetical generating gears. This abstraction introduces an inherent geometric inconsistency between the theoretical cutting edge and the true conical rake surface of the cutter, limiting prediction accuracy and hindering measurement-driven compensation. To address this limitation, this study proposes a unified analytical and measurement-driven framework for cylindrical gear skiving that eliminates the generating-gear assumption entirely. A direct surface-based meshing formulation is developed by enforcing positional coincidence and tangential compatibility directly on the cutter’s conical rake surface, ensuring strict geometric consistency with the physical cutting mechanism. To incorporate real cutter deviations, a tension-controlled spline reconstruction method is introduced to recover smooth and curvature-stable cutting edge curves from noisy three-dimensional measurement data, overcoming the oscillation and instability commonly associated with high-order polynomial fitting. By integrating direct surface-based meshing, spline-regularized reconstruction, and CNC-oriented kinematics within a single formulation, this work establishes a complete digital chain for precision skiving cutter modeling, simulation, and compensation, providing a practical foundation for advanced tool design and manufacturing optimization.