Surface-centric toolpath optimization via cutter location surface reconstruction for addressing neighboring inconsistency in CNC machining

Abstract

In complex surface machining, traditional path-centric computer-aided manufacturing (CAM) and computer-numerical-control (CNC) research only process surface-discretized information, inherently relying on geometric line-based algorithms. Due to their loss of surface continuity during machining, significant feedrate variations occur between neighboring toolpaths, leading to neighboring-inconsistency defects that compromise surface quality in industrial applications. To address this long-overlooked issue, this paper proposes a novel surface-centric information processing framework for toolpath optimization. First, the cutter location (CL) surface is defined and utilized as a carrier of continuous surface-level information. An optimal fitting method based on a dual-objective combined metric in quadratic form is proposed to reconstruct unordered CL points into a G2-continuous B-spline CL surface, which balances accuracy and smoothness. The reconstructed CL surface maintains continuous longitudinal curvature. Subsequently, the correlation between longitudinal curvature distribution and feedrate consistency is investigated. A curvature-consistent toolpath generation algorithm is introduced, which preserves the original path structure while leveraging the theoretical longitudinal curvature of the CL surface to select new CL points and minimize discrete curvature estimation errors. Machining experiments conducted on a mountain-shaped surface and a human-face surface validate the effectiveness of the proposed method. By extracting and reusing surface-level information, the optimized toolpaths significantly improve neighboring feedrate consistency, enhance surface quality, and reduce machining time. The proposed method is fully compatible with existing CAM-CNC pipelines, requiring no hardware modifications, thus demonstrating high industrial adaptability.