A Confidence Interval-Based Process Optimization Method Using Second-Order Polynomial Regression Analysis

Influence of Selective Laser Melting Additive Manufacturing Parameters in Inconel 718 Superalloy

Selective laser melting (SLM) is one of the most reliable and efficient procedures for Metal Additive Manufacturing (AM) due to the capability to produce components with high standards in terms of dimensional accuracy, surface finish, and mechanical behavior. In the past years, the SLM process has been utilized for direct manufacturing of fully functional mechanical parts in various industries, such as aeronautics and automotive. Hence, it is essential to investigate the SLM procedure for the most commonly used metals and alloys. The current paper focuses on the impact of crucial process-related parameters on the final quality of parts constructed with the Inconel 718 superalloy. Utilizing the SLM process and the Inconel 718 powder, several samples were fabricated using various values on critical AM parameters, and their mechanical behavior as well as their surface finish were examined. The investigated parameters were the laser power, the scan speed, the spot size, and their output Volumetric Energy Density (VED), which were applied on each specimen. The feedstock material was inspected using Scanning Electron Microscopy (SEM), Energy-dispersive X-ray spectroscopy (EDX) analysis, and Particle-size distribution (PSD) measurements in order to classify the quality of the raw material. The surface roughness of each specimen was evaluated via multi-focus imaging, and the mechanical performance was quantified utilizing quasi-static uniaxial tensile and nanoindentation experiments. Finally, regression-based models were developed in order to interpret the behavior of the AM part’s quality depending on the process-related parameters.