Pulsed laser micro polishing: Surface prediction model

Abstract

The objective of this work is to predict the final roughness of metal surfaces that have undergone pulsed laser micro polishing. The motivation for pulsed laser micro polishing is to reduce the surface roughness of parts whose surface texture can approach the feature size. Being able to predict the magnitude of the polishing and frequency (wavelength) content of the surface will assist in the design of optimal processing parameters with minimal experiments. Laser pulses are used to create shallow melt pools with a controlled size (e.g., depth) and duration in order to allow surface tension forces to “pull down” asperities with small radius of curvature. There is no ablation occurring in the process being modeled. The melt depth and duration are predicted with a transient, two-dimensional axisymmetric heat transfer model with temperature-dependent material properties. The surface of the melt pool is analytically modeled as oscillations of stationary capillary waves with damping resulting from the forces of surface tension and viscosity. Above a critical spatial frequency, fcr, a significant reduction in the amplitude of the spatial Fourier components is expected. The work described in this paper extends the concept of critical frequency to a physics-based prediction methodology for predicting the spatial frequency content and surface roughness after polishing, given the features of the original surface, the material properties, and laser parameters. The proposed prediction methodology was validated using line polishing data for stainless steel 316L and area polishing results for pure nickel, Ti6Al4V, and Al-6061-T6. The predicted average surface roughnesses were within 12% of the values measured on the polished surfaces.