Collaborative optimization of conical cutter sequence for efficient multi-axis machining of deep curved cavities

As an essential part of the composite fan blade, the leading edge protection cap (LPC) has a very narrow and deep cavity which, in order to avoid the interference, requires the conical ball-end cutter to be long and thin. It calls to improve the cutter's stiffness so to increase the roughing efficiency of the whole cavity. Targeting this important problem, this paper proposes a novel method to collaboratively optimize a conical cutter sequence, the machining ranges, and the cutting parameters for achieving the highest material removal efficiency. The main difficulty is that all the relevant entities – i.e., the LPC cavity geometry, tool size, tool axis, machining ranges, minimum tool length, tool stiffness, and cutting performance – collaboratively affect the total cutting efficiency. To facilitate decoupling them, the 3D LPC cavity is characterized by its medial surface. To identify all the geometrically accessible conical tools of each medial point, an efficient algorithm is proposed, which is featured by searching characteristic points on the cavity surface. By considering both the geometric and physical accessibilities, the tool sequence domain is constructed. To obtain the appropriate cutting parameters, the best cutting performance of a weak conical cutter is modeled under the constraint of deflection due to the cutting force. Finally, the complicated collaborative optimization model aiming for the minimum cutting time is established and solved by a PSO-based algorithm. The experimental results confirm that the proposed model and algorithm are practicable for improving the roughing efficiency of LPC cavity.