A Novel Additive Manufacturing Process Metric for Predicting Spatter-Related Porosity in Laser Powder Bed Fusion

Components fabricated using the powder bed fusion laser beam metallic (PBF) additive manufacturing (AM) process comprise a multitude of sequential weld passes. Porosity defects resulting from weld pass inconsistencies are a concern for PBF materials and have a strong adverse effect on the mechanical properties. In an effort to understand and avoid spatter-induced porosity, this work aims to provide a novel computational technique that can be used to quantify and predict the sequence-sensitive impact of spatter upon the PBF process stability and consequential porosity in as-printed material. A novel spatter impact AM model-based process metric (AM-PM) is introduced to model and quantify the impact that spatter has on the PBF process. The occurrence of spatter-induced porosity is studied using thermal rise, lack of fusion, and spatter impact AM-PMs synchronized with porosity measured by high-resolution X-ray computed tomography. Six cylindrical specimens were designed to compare the AM-PM correlations with porosity across two different laser powers and three hatch scanning strategies. A point field-based computational approach is shown to be effective for testing the influence of different AM-PMs and interrogating the physical process conditions underlying the porosity formation. Further, characterization using optical metallography and scanning electron microscopy indicated that both keyhole and lack of fusion porosity correlated with the spatter impact AM-PM, which can be exploited to predict and control spatter-related porosity by the hatch strategy. Efforts to predict porosity composition within PBF material should incorporate the PBF process disturbances that can result from spatter. The spatter impact AM-PM can be readily incorporated into the development of defect prediction models at the part scale.