| description abstract | Face milling is not only a primary machining technique for the mass production of bevel gears, but it has also become a standardized process integrated into computer numerical control (CNC) bevel gear-cutting machines in the last two decades. Controlling suitable feed rates for face milling is one of the most direct and pivotal factors influencing processing efficiency for CNC machines. Despite being programmed through numerical codes, the feed rates provided by the gear machines most rely on experiential insights rather than optimization. Therefore, leveraging material removal rate (MRR) directly correlates with machining power and will hold immense potential for optimizing feed rates and enhancing efficiency. Because commercial software solutions cannot accurately predict the MRR for face milling operations, this paper uses a novel ring-dexel-based model for cutting simulation to address this issue. The main aim of this model is to provide a more precise prediction of the MRR across all face milling cuttings. By controlling the cutting depth and generating angle, the ring gear's plunging process and the pinion's single-roll generating process were successfully simulated. Thus, the MRRs through all cutting processes were calculated. Experimental results showed that tool torques are positively correlated with the MRRs. Finally, by appropriately increasing the cutting feed rate based on the MRR, the pinion and ring gear machining times were reduced by 44% and 18%, respectively. | |
