An economical sculptured surface machining approach using fuzzy models and ball-nosed cutters

Assigning a constant feedrate for a ball-nosed cutter in the manufacturing of sculptured surfaces cannot achieve an optimum material removal rate (MRR). This is because the actual cutting speed on the cutting edges of the cutter is varying due to the change of surface gradient. In addition, the cutting force cannot be maintained at a constant level when the cutting speed changed. In this study, a fuzzy based MRR optimization approach is proposed in order to increase the machining efficiency. An optimum feedrate for each cutting point in the machining of sculptured surfaces is calculated, and the cutting force is kept constant. The surface gradient and tool life are treated as the fuzzy input variables. A machining trail demonstrated that the MRR was increased by 41% in comparison with the conventional constant feedrate cutting for the same surface.