From accurate stability prediction to efficient pitch angle optimization: a workpiece-dominated dynamics approach for thin-walled blade finishing

Thin-walled blades are critical components in aero-engines, yet their milling processes are highly susceptible to chatter, which severely compromises machining precision and surface quality. Although variable-pitch ball-end cutters offer a viable solution, their optimization for chatter suppression often lacks efficiency and adaptability. To address this issue, we adopt a workpiece-dominated dynamics approach (emphasizing the dominant role of the workpiece's dynamic behavior in milling processes for stability) by developing a physics-based, phased optimization strategy. This strategy directly determines the optimal pitch angle distribution, bypassing the computationally intensive processes of calculating Floquet multipliers and iteratively solving Stability Lobe Diagram (SLD). Moreover, it accounts for the effects of forced vibrations arising from the inherently weak rigidity of thin-walled blades, thus achieving superior optimization performance. To enable accurate stability prediction for the optimized tool, we establish a high-fidelity, multi-time-delay dynamic model that explicitly incorporates location-dependent modal parameters (i.e., position-dependent mode shapes), elastic deformation, and material removal effects. This enables location-specific, precision-oriented stability prediction and moves beyond traditional tool-centric analyses. Milling experiments and surface roughness characterization confirm that the proposed methodology significantly improves stability limits, expanding the stable spindle-speed range by 17–25% across various blade heights, thereby enhancing machining precision and surface quality. This work provides a reliable theoretical foundation and a practical tool-design methodology for vibration-free, high-precision milling of flexible thin-walled parts.