Influence of internal and surface defects on the fatigue performance of additively manufactured stainless steel 316L

The additive manufacturing (AM) process generates new material challenges with associated features like internal defects and inherent surface roughness, reducing fatigue performance. This paper introduces a new approach to characterizing internal defects and surface irregularities of additively manufactured stainless steel 316L samples using X-ray computed tomography (XCT). This method overcomes the limitations of previous methods and can effectively provide holistic information on the surface topologies of AM components. An equivalent defect size, root area(eff), based on defects' features and the interaction of internal and surface imperfections, is proposed for fatigue life and failure origins prediction.