Abstract

One of the main challenges encountered in the Laser-based Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) process is the fabrication of defect-free parts. The presence of defects severely degrades the mechanical performance of AM parts and especially their fatigue strength. The most popular and reliable method to assess the ability of the employed process parameters for the fabrication of full-density parts is the process windows map, also known as printability map. However, the experimental procedure for the design of the printability maps and the identification of the optimum-density process parameters is usually time-consuming and expensive. In the present work, a modelling framework is presented for the determination of a printability map and the optimization of the L-PBF process based on the prediction and characterization of melt-pool geometric features and the prediction of porosity of small samples of 316L SS and Ti-6Al-4V metal alloys. The results are compared with available experimental data and present a good correlation, verifying the modelling methodology. The suitability of the employed defect criteria for each material and the effect of the hatch-spacing process parameter on the optimum-density parameters are also presented.