Flank tool wear prediction of laser-assisted milling

Abstract

An analytical predictive model for flank tool wear in laser-assisted milling is proposed based on the principles of abrasive, adhesive, and diffusive wear. The laser effect is included by treating the laser beam as a heat source on top surface. Heat convection between top surface and the environment is factored into account. Isothermal boundary conditions are assumed for the laser-affected area. The laser preheating temperature field is averaged along the tool-workpiece interface as initial temperature. Next, the milling configuration is treated as orthogonal cutting followed by angular-dependent coordinate transformation at each instance. The effective force due to flank wear is calculated by integrating the stress component along the chip cross section and wear land, and the average stress on tool-workpiece interface due to flank wear is calculated based on the effective force and contact area. The average temperature along the interface is derived through imaginary heat source method with secondary and rubbing heat sources considered. The flank wear rate prediction considers abrasion, adhesion, and diffusion. The proposed model is validated through experimental measurements on the laser-assisted milling of K24 nickel-based superalloy, and a sensitivity analysis with respect to three cutting and two laser parameters is conducted. The proposed predictive model is able to match the wear progressions during steady state wear region in less than two minutes with high accuracy of 6.48% error on average. Therefore, it is valuable for providing a fast, credible, and physics-based method for the prediction of flank tool wear in laser-assisted milling of various materials. Through sensitivity analysis, the model is able to guide the selection of cutting and laser parameters when the flank tool wear is the main concern.