Improving X-ray CT porosity analysis towards enhanced in-situ monitoring and real-time defect prediction in metal laser powder bed fusion

Laser powder bed fusion of metals enables the fabrication of complex components but is prone to defects such as porosities, which can compromise part integrity. This study introduces a novel reference object designed to enhance the traceability of porosity measurements via X-ray computed tomography. A data fusion strategy combining optical profilometry and computed tomography was implemented to calibrate defects resembling typical PBF-LB/M porosities. A new segmentation method, named advanced local-adaptive, demonstrated improved accuracy over existing algorithms. This approach enables the generation of reliable porosity reference data to support the development of advanced methodologies for in-process monitoring and real-time defect size prediction.