As important components of gas turbine engines, axial-flow compressors have been improved with a more complex and accurate airfoil design to meet high aerodynamic requirements; specifically, the pressure and suction surfaces of the airfoils (or blades) are now represented with free-form surfaces in CAD software systems. Since quality of the blades affects efficiency of the engines and safety of the aircrafts, some types of compressors are produced with the blades and the hub as a single piece on 4-axis CNC milling machines. However, it is still quite challenging to automatically determine cutter sizes and orientations without gouging and interference during the 4-axis milling, because the geometric shape of the blades is complex and the blades overlap with each other. As a result, the established method of determining tool size and orientation in industry is by trial and error in a repetitive process of selecting cutters and planning tool-paths with CAM systems. To address this problem, a novel approach is proposed to automatically determine cutter sizes and orientations for 4-axis milling of the axial-flow compressors blades without gouging and interference. The main contribution of this work is that (1) a mathematical model for optimizing cutter sizes in 4-axis milling is established; and (2) by applying a global optimization method — the particle swarm optimization method — to this model, the maximum allowable size of a cutter and its corresponding orientation can be found at each cutter-contact (CC) point on the surface being machined. Therefore, all the maximum allowable sizes of cutters for all the CC points and the corresponding cutter orientations can be computed. A group of standard cutters are then selected; each of which can sweep particular CC points without damaging the compressor. Since it is efficient and reliable, this newly proposed approach can be directly implemented in commercial CAD/CAM software systems to benefit the manufacturing industry.

This content is only available via PDF.
You do not currently have access to this content.