Governing of Melt Pool Solidification Parameters and Microstructure Evolution Indicator During SLM‐Ti6Al4V Alloy Through Parametric Sweep Optimization

Abstract

Selective laser melting (SLM) process offers a versatile additive manufacturing technology. However, the wide range of process parameters and complex thermophysical phenomenon necessitate optimization of process parameters for obtaining a high‐quality finished product. The optimization of process parameters through experiment is expensive and time‐consuming. On the other hand, computational approaches offer a fast and economical way to predict the contributions of process parameters. In this article, therefore, a multiphysics finite‐element model and phase‐filed model of solidification process were used to investigate the effects of process parameters on the melt pool solidification parameters and microstructure evolution of SLM‐Ti6Al4V process. Simulations were performed using the single‐level setup method followed by a parametric sweep optimization (PSO) approach that helped identify the best‐suited process parameters. Through the PSO, reductions in temperature gradient by 9.7% and 13.7%, and cooling rate by 23.6% and 14.3% were found at a fixed laser scan speed and laser power, respectively. The associated solidification morphology factor was found to be 5.8 × 105 Ks/m2. In addition, the primary dendrite arm spacing (PDAS) was found to be at 3.6% and 6.8% increments at a fixed laser speed and laser power, respectively. Finally, optimal results of the solidification parameters were compared with the existing data to validate the approach. The simulation results have been shown that reduction in the temperature gradient by 28.5%, cooling rate by 48.6%, and solidification morphology factor by 3.3% tend to minimize fluctuation of melt pool. The comparisons have also shown that the PSO approach is effective and accurate for predicting the solidification behaviors of SLM‐Ti6Al4V process.