A comparative study of sharp and round-edge tools in machining with built-up edge formation: cutting forces, cutting vibrations, and neural network modeling

摘要

The tool edge radius significantly affects material deformation and flow, tool-chip friction, and a variety of machining performance measures (such as the cutting forces and tool wear) in mechanical micro/meso-scale machining. The tool edge-related research, either theoretically or experimentally, has been only focused in machining cases in which no built-up edge (BUE) is generated. To close this research gap, a comparative study of sharp and round-edge tools in orthogonal machining with BUE formation is conducted, including both experimental investigations and theoretical modeling. The experimental results show that the variations of the cutting forces are more stable in machining with a sharp tool than those in machining with a round-edge tool. A round-edge tool produces higher vibration magnitudes than does a sharp tool. The cutting vibrations do not necessarily have the same varying pattern as that of the cutting forces in machining with either a sharp tool or a round-edge tool. A neural network-based theoretical model is developed to predict three distinct regions of BUE formation (namely BUE Initiation Region, Steady BUE Region, and Unsteady BUE Region) in machining with a round-edge tool. The developed neural network model has been proven valid using a separate set of cutting experiments under different cutting conditions from those used for network training and testing.