Slip line modeling of machining with worn blunt cutting tools.

摘要

Majority of researchers believe that the flank wear direction is parallel to the cutting velocity. Although some researchers doubt this and pose an argument about this in theory, no research available provides direct experimental evidence to support this. This research has used the white light interferometry microscope to capture the included angle between tool's rake face and wear land. By discounting all the possible causes in the experimental setup that might change the rake face and cutting velocity direction, the nonzero angle is found between the tool's wear land and the cutting velocity direction. This verifies the opinion that the flank wear is sloping downward away from the cutting edge.;Flank wear of a cutting tool alters the microgeometry of the cutting edge from its initial "fresh-tool" state. Many cutting tools are manufactured with an edge radius (bluntness) on the cutting edge to help protect the edge from chipping. So, the overall edge condition that affects forces, power, residual stress and other performance measures is a combination of the edge radius and wear land.;Slip-line field theory has been successfully applied to many plane strain metal-forming processes to obtain the analysis of work material deformation and to determine the distributions of stress and velocity in the plastic deformation zone. Machining process as a two-dimensional problem of steady motion uses the slip-line field solution to predict loads and deformation modes. This work, in conjunction with the slip-line field theory, investigates the workpiece deformation modes based on the photos of fresh/worn edge-radiused tools during/after cutting, and also based on the force-vs-wear data for larger and smaller edge radii. It is found that the tools' geometry (e.g., the inclination angles of tool's edges) and friction stresses on the boundary of the tools all change with the wear length exponentially. So do the shear flow stresses in the primary deformation zone and under the wear land. Based on some select data available, the exponential model can be used for these values, making this model predictive.