Abstract

Abstract The optimization of selective laser melting (SLM) process parameters for a new material through experiments is a time-consuming and challenging process. Computational approaches, on the other hand, offer an economical and relatively faster approach to effectively predict the influences of process factors on the behaviors of the field variables of SLM process. In this work, multiphysics models built using COMSOL software were used to carry out optimization of SLM-Ti6Al4V processes through a single-level setup method followed by a parametric sweep optimization (PSO) approach. The simulated results of the melt pool field variables obtained from both approaches were compared. In the PSO approach, the melt pool velocity was found to have 14.3% higher flow and 78.8% reduction in the transient velocity fluctuation amplitude within the melt pool region. The average transient temperature of the melt pool region was found to have 5.9% increase and 36.4% reduction in the average fluctuation amplitude along the solidus and peak points, respectively. On the other hand, the associated temperature gradient was found to have a fluctuation amplitude reduction of 15.3% at the maximum side of the melt pool region. Finally, the optimal solutions of the melt pool field variables obtained from the PSO were compared with published data to verified the approach. The reductions in temperature and thermal gradient results were found by 18.3% and 28.5% respectively in the melt pool region of the current SLM-Ti6Al4V process and, hence, validating the predictions of the PSO technique.

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