Anomaly detection by X-ray tomography and probabilistic fatigue assessment of aluminum brackets manufactured by PBF-LB

The assessment of safety-critical components for fatigue applications is a key requirement for metal additive manufacturing (AM) applications. Material anomalies play a relevant role in determining the fatigue resistance properties of a component. X-ray computed tomography (CT) helps collect important information on these flaws, such as their size and position within a part. In this study, we discuss how to employ anomaly data detected on an AlSi10Mg bracket manufactured by laser- powder bed fusion to describe the prospective allowable life of a component under a given operating condition. A statistical analysis was conducted on the specimens and component to derive the correlation between different resolution scans and analyze the uncertainties of the micro-CT measurements. The full-scale non-destructive evaluation (NDE) can be constrained to large voxel sizes. Eventually, the authors proposed a fully probabilistic route for assessment instead of a simple deterministic assessment based on safety factors. This assessment enables designers to consider the uncertainties of the assessment (uncertainties of micro-CT detection and the model for fatigue strength).