Multi-objective optimization of laser milling of 5754 aluminum alloy

Abstract

Laser milling is a new, very flexible process for micro-fabrication, suitable for machining difficult-to-machine materials, like ceramics, dielectrics, carbide and hardened steel with good productivity and surface. Optimal selection of process parameters is highly critical for successful material removal and achieving high surface quality. It is crucial for Laser Milling to enhance the productivity of the process in terms of maximization of the material removal rate (MRR), calculated as the ratio between the volume of removed material and the process time, saving at the same time a good surface quality, and to correlate this index to the ablation depth and to surface roughness. In contrast, laser ablation suffers from the usual incompatibility of high ablation depths and good surface quality. The objective of this paper was to demonstrate that the careful laser choice and process optimization can result in a satisfactory compromise for both. This goal was achieved with a simultaneous statistical analysis of ablation depth, material removal rate and surface roughness. Moreover, a multi-objective statistical optimization was performed for improving machining productivity and surface quality. The dependence of the ablation depth, MRR and surface roughness on the laser fluence was also analyzed. All experimental tests were conducted on the 5754 aluminum alloy using a nanosecond Nd:YAG laser with a wavelength of 1064nm.