Killer notches: The effect of as-built surface roughness on fatigue failure in AlSi10Mg produced by laser powder bed fusion

Additive manufacturing allows the production of complex components for critical applications such as in the aerospace industry. Laser powder bed fusion is the most widely used form of additive manufacturing and good progress has been made in improved material quality in recent years. Despite the progress, fatigue properties are sometimes still problematic and this requires further investigation. The fatigue properties of additively manufactured metals depend on a variety of factors including surface roughness, microstructure, porosity and residual stress, amongst others. In this work the role of surface roughness in particular is evaluated using micro computed tomography (microCT) scans before and after fatigue tests. The crack locations are identified in scans after fatigue testing and correlated with surface features prior to fatigue tests by careful alignment of CT images. In this way notches on the surface which act as “killer notches” are measured and compared with other defects (both roughness notches and pores) in the vicinity. Direct evidence is thereby provided for specific features acting as killer defects, studied with varying surface topographies depending on build orientation. A statistical analysis using stress intensity factor and fatigue test results of the same samples directly validate the effect of the notches, in comparison to other similar notches across the sample. This is the first notch-based surface roughness evaluation method reported using X-ray tomography, showing promise as analytical methodology. In addition, the experimental campaign shows for the first time a direct correlation of fatigue strength with surface roughness using different typical as-built surfaces. This work lays the foundation for improved non-destructive testing, predictive modelling and overall improvement and management of the performance of additively manufactured parts based on surface features and surface characterization.