Ultrasonic Signal Response from Internal Manufactured Defects in Laser- Based Powder Bed Fusion (PBF-LB) Manufactured superalloys

Sammanfattning

Additive manufacturing (AM) is an advanced technology reshaping global productfabrication by enabling lightweight and complex structures directly from CAD models[1]. While AM provides design freedom and material efficiency, challenges remainin ensuring consistent quality, as defects such as porosity, microcracks, and lack offusion (LOF) voids can degrade mechanical performance [7–9]. Non-destructive testing(NDT) methods are therefore critical, with X-ray Computed Tomography (XCT)and Ultrasonic Testing (UT) emerging as the most promising despite limitations ofcost, speed, and geometry sensitivity [16,20]. UT, in particular, enables early detectionof internal flaws without damaging the component, and recent advances such asphased array and laser-based techniques are expected to further enhance inspectioncapability [2,24,25].This study evaluates the ultrasonic signal response from intentionally introduceddefects in PBF-LB manufactured Alloy 247 and Inconel 939 samples. Both immersionUT and PAUT were applied to investigate the influence of defect morphology,orientation, and surface finish. Results showed that defects down to 0.4 mm couldbe reliably detected when oriented perpendicular to the scanning surface. Machinedsurfaces significantly improved defect detectability, while partially melted powderaround defects increased scattering and reduced signal clarity. Among probes, the3.25" transducer provided the most consistent response due to its larger aperture,which enhanced beam focus, signal strength, and defect detectability across variedgeometries and surface conditions. Defect morphology strongly influenced detectability,with angled and roof-shaped defects showing reduced visibility comparedto cylindrical or spherical ones.Comparison of inspection methods demonstrated that PAUT enhanced sensitivityand imaging in geometrically complex regions, whereas XCT provided more accuratedefect characterization but with slower scan speed and higher cost. These findingshighlight the importance of probe selection, surface condition, and defect morphologyfor developing robust in-situ inspection strategies and support the integrationof PAUT and XCT as complementary methods for standardized quality control inmetal additive manufacturing.