000161775 001__ 161775
000161775 005__ 20251017144618.0
000161775 0247_ $$2doi$$a10.1016/j.matdes.2025.114057
000161775 0248_ $$2sideral$$a144382
000161775 037__ $$aART-2025-144382
000161775 041__ $$aeng
000161775 100__ $$aHolgado, Ibon
000161775 245__ $$aMetrological evaluation and classification of porosity in metal additive manufacturing using X-ray computed tomography
000161775 260__ $$c2025
000161775 5060_ $$aAccess copy available to the general public$$fUnrestricted
000161775 5203_ $$aEnsuring the structural integrity of metal additive manufacturing (AM) components is challenging due to inherent porosity, which critically affects mechanical performance. The impact of porosity depends on its morphology, determined by the formation mechanism, making it a core focus for characterization and classification through advanced non-destructive testing methods. This study introduces a novel X-ray computed tomography (XCT) based methodology for the metrological assessment of porosity in laser powder bed fusion manufactured AlSi10Mg components. A new modular artefact, specifically designed to contain real porosity, enables the application of the substitution method for porosity characterization, including the assignment of measurement uncertainty, representing a novel application for evaluating real porosity morphology using XCT. Advanced porosity analysis algorithms, including ’VGDefX’, ’OnlyThreshold’, and ’VGEasyPore’, are benchmarked to determine the one yielding the lowest dimensional measurement uncertainty across varying material thicknesses. The VGDefX algorithm, which incorporates a probability-based and iterative approach, demonstrates superior repeatability, achieving subvoxel systematic errors and measurement uncertainties for dimensions exceeding five times the voxel size. Based on the pore characterization results, a classification methodology using the most discriminating porosity parameters is developed. Leveraging volumetric mean gray value, this method distinguishes over-melting from under-melting porosity in a real component with >95 % accuracy.
000161775 536__ $$9info:eu-repo/grantAgreement/ES/AEI/PID2020-118478RB-100
000161775 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000161775 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000161775 700__ $$aOrtega, Naiara
000161775 700__ $$0(orcid)0000-0001-7152-4117$$aYagüe-Fabra, José A.$$uUniversidad de Zaragoza
000161775 700__ $$aPlaza, Soraya
000161775 700__ $$aVillarraga-Gómez, Herminso
000161775 7102_ $$15002$$2515$$aUniversidad de Zaragoza$$bDpto. Ingeniería Diseño Fabri.$$cÁrea Ing. Procesos Fabricación
000161775 773__ $$g254 (2025), 114057 [17 pp.]$$pMater. des.$$tMaterials & design$$x0264-1275
000161775 8564_ $$s13415621$$uhttps://zaguan.unizar.es/record/161775/files/texto_completo.pdf$$yVersión publicada
000161775 8564_ $$s2462574$$uhttps://zaguan.unizar.es/record/161775/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000161775 909CO $$ooai:zaguan.unizar.es:161775$$particulos$$pdriver
000161775 951__ $$a2025-10-17-14:20:33
000161775 980__ $$aARTICLE