A computational model to predict surface roughness in laser surface processing of mild steel using nanosecond pulses

Surfaces processed by scanning with a pulsed laser have an inherent roughness due to the partial overlap of discreet pulses. Experimentally optimising the parameters to minimize roughness is challenging because of the time and effort required. A computational model based on the finite volume method for predicting surface roughness during laser surface processing is presented in this work. The data obtained from a single pulse model is used to predict the surface profile by overlapping the successive pulses based on scanning speed. The model captures numerous physical phenomena such as laser absorption, heating, melting, vaporisation, plasma effects, melt pool flow and solidification, as well as the effect of laser scanning. The surface roughness values (Ra and Rq) obtained using the model are reasonably within the limits of the experimental data. The results reveal that the effect of laser parameters on surface roughness is non-linear. While the ablation depth increases exponentially with a decrease in scan speed, the local maximum and minimum of surface roughness could be in the parameter range's intermediate values. The model developed in this work can be used to optimise the processing time and surface finish in different laser-based surface processing techniques.