Identification of depth-of-cut variations and their effects on the process monitoring for the end milling process.

摘要

Knowledge of depth-of-cut (DOC) variations is very important because it is one of the major reasons for false alarms arising in process monitoring systems, and it is very important to quality control processes and their products. In this thesis, two generalized methodologies have been proposed for the identification of DOC variations for different cutting conditions in the end milling process.; The first methodology specifically applies to a rigid end mill cutter where cutter deflection is negligible. The rigid end milling force model is assumed and the cutter geometries are assumed constant during cutting. The DOC variations are detected based upon force shape characteristics analysis and the associated force indices. Cutting forces are analyzed and classified to three cutting types and four degrees of overlap. Characteristic equations are derived to establish relationships between the force indices and DOC variations for each cutting type and degree of overlap. Experimental validation results show the methodology can accurately detect DOC variations when the cutter deflection is negligible.; In situations where significant cutter deflection is present, a fully-flexible mechanistic end milling force model is proposed to generate simulated force profiles for the DOC variation estimation. The end mill cutter is discretized as a series of elliptical disc elements. Effective cutter geometries, viz., effective helix angle and effective normal rake angle are obtained by investigating the effects of cutter deflection on each disc element. The flexible cutting force is achieved by iteratively solving for chip load that balances the force, cutter deflection and effective cutter geometries. The fully-flexible end milling force model is then applied to the DOC variation detection methodology by constructing force indice databases to relate the force indices to DOC variations. Experimental validation results show that when significant cutter deflection is present in cutting, the fully-flexible end milling force model can significantly improve the accuracy of force prediction in both the magnitude and shape characteristics comparing to other force models; and the DOC variation detection methodology employing the fully-flexible end milling force model can significantly reduce the DOC variation estimation errors comparing to those methodologies employing other force models.