A Melt Pool Temperature Model in Laser Powder Bed Fabricated CM247LC Ni Superalloy to Rationalize Crack Formation and Microstructural Inhomogeneities

This study of the laser powder bed fusion (LPBF) of γ′-strengthened Ni superalloy CM247LC focuses on the development of a melt pool temperature model to predict crack density within the alloy. This study also analyzes spatter and elemental evaporation, which might cause defects and inhomogeneities, at different melt pool temperatures. The melt pool temperature model provides more accurate predictions than the widely used energy density model. Spatter particles were collected and characterized to study their sizes and chemical compositions, compared with the virgin powder, recycled powder, and as-built samples, to probe the impact of their entrapment into the melt pool. This study also investigated Al evaporation, revealing that its extent does not correlate with the laser energy density and is believed to be rather limited by comparing the chemistry of the virgin powder and the build. Last, the impact of LPBF process parameters on the formation of these inhomogeneities, and accordingly crack formation, was studied using finite element analysis by estimating the maximum melt pool temperature and correlating it with the formation of the microstructural inhomogeneities. The morphology of the various cracking modes was associated with the process parameters.

Selective Laser Melting of 316L Austenitic Stainless Steel: Detailed Process Understanding Using Multiphysics Simulation and Experimentation

The parameter sets used during the selective laser melting (SLM) process directly affect the final product through the resulting melt-pool temperature. Achieving the optimum set of parameters is usually done experimentally, which is a costly and time-consuming process. Additionally, controlling the deviation of the melt-pool temperature from the specified value during the process ensures that the final product has a homogeneous microstructure. This study proposes a multiphysics numerical model that explores the factors affecting the production of parts in the SLM process and the mathematical relationships between them, using stainless steel 316L powder. The effect of laser power and laser spot diameter on the temperature of the melt-pool at different scanning velocities were studied. Thus, mathematical expressions were obtained to relate process parameters to melt-pool temperature. The resulting mathematical relationships are the basic elements to design a controller to instantly control the melt-pool temperature during the process. In the study, test samples were produced using simulated parameters to validate the simulation approach. Samples produced using simulated parameter sets resulting in temperatures of 2000 K and above had acceptable microstructures. Evaporation defects caused by extreme temperatures, unmelted powder defects due to insufficient temperature, and homogenous microstructures for suitable parameter sets predicted by the simulations were obtained in the experimental results, and the model was validated.

In-situ monitoring of optical emission spectra for microscopic pores in metal additive manufacturing Submitted for Publication

Quality assurance techniques are increasingly demanded in additive manufacturing. Going beyond most of the existing research that focuses on the melt pool temperature monitoring, we develop a new method that monitors the in-situ optical emission spectra signals. Optical emission spectra signals have been showing a potential capability of detecting microscopic pores. The concept is to extract features from the optical emission spectra via deep auto-encoders, and then cluster the features into two quality groups to consider both unlabelled and labelled samples in a semi-supervised manner. The method is integrated with multitask learning to make it adaptable for the samples collected from multiple processes. Both a simulation example and a case study are performed to demonstrate the effectiveness of the proposed method.