Improving Deposited Surface Quality in Additive Manufacturing Using Structured Light Scanning Characterization and Mechanistic Modeling

Abstract

The surface quality of parts fabricated using laser-directed energy deposition additive manufacturing significantly affects the fatigue life, corrosion resistance, and performance of the components. Surface quality improvements remain a key challenge in laser-directed energy deposition because of the involvement of multiple simultaneously occurring physical phenomena controlling the surface characteristics. Here, a unique combination of structured light scanning characterization and mechanistic modeling was used to identify three key physical factors that affect surface quality. These factors include a geometric factor, an instability factor, and a disintegration factor, which were calculated using a mechanistic model and correlated with the surface characteristics data obtained from the structured light scanning characterization. It was found that these factors can precisely explain the variations in the average surface roughness. In addition, skewness and kurtosis of the surfaces made by laser-directed energy deposition were found to be significantly better than those observed in traditional manufacturing. Based on the experimental and modeling results, a surface quality process map was constructed that can guide engineers in selecting appropriate sets of process variables to improve deposit surface quality in additive manufacturing.