Laser powder bed fusion (PBF-LB/M) is a metal-based additive manufacturing (AM) process that utilizes a laser to melt powder particles selectively and form the desired product through a layer-by-layer fabrication process. It can produce parts with far greater geometrical complexity than traditional methods, however, PBF-LB/M induces inevitable microstructural defects, such as voids and pores, that can adversely affect the quality and performance of the manufactured components. Hence, knowledge of pore formation, types, and suppression is essential for successful future AM applications. This research investigates the formation of different types of pores and their quantification from X-ray micro-computed tomography images of a formerly reported sample [1]. It also examines the influence of the volumetric energy density (VED) on the size, shape, and location of pores for 316L stainless steel parts produced by the PBF-LB/M process.

Several studies have focused on exploring and explaining the types of pores in the PBF-LB/M process. Soda et al. [2] present an overview of the formation, detection, and quantification of pores in AM. Nudelis et al. [3] study to quantify a new approach of pores classification. Our research differs from previous studies as we study different phase-space variables to determine the existing types of pores and quantify them at different volumetric energy densities of the laser.

In the poster, we show the percentage (of numbers) of the different types of defects present in AM components based on selection cuts on the phase space of sphericity and height of the pores along the Z axis. The small-elongated types of events might be artifacts such as cone beam artifacts arising from the XCT scan. The porosity increases with increasing VEDs for all types of pores. The keyhole types of pores depend more on VED and dominate at high VED. The nature of large spherical pores that might be due to the coalescence of micropores or the collapse of large keyholes is still under further investigation.

References

[1] S. Oster et al. “On the Registration of Thermographic in Situ Monitoring Data and Computed Tomography Reference Data in the Scope of Defect Prediction in Laser Powder Bed Fusion.” Metals 12.6 2022, 947

[2] A. Sola and A. Nouri. "Microstructural porosity in additive manufacturing: The formation and detection of pores in metal parts fabricated by powder bed fusion." Journal of Advanced Manufacturing and Processing 1.3, 2019, e10021.

[3] N. Nudelis and P. Mayr. "A novel classification method for pores in laser powder bed fusion.", Metals 11.12, 2021, 1912.