“Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) fabricates 3D metal parts layer-by-layer. The process enables production of geometrically complex parts that are difficult to inspect with traditional methods. The LPBF parts experience significant geometry driven thermal variations during manufacturing. This creates microstructure and mechanical property inhomogeneities and can stochastically cause defects. Mission critical applications require part qualification by measuring the defects non-destructively. The layer-to-layer nature of LPBF permits non-intrusive measurement of radiometric signals for a part’s entire volume. These measurements provide thermal features that correlate with the local part health. This research establishes Optical Emission Spectroscopy (OES) and Short-Wave Infrared (SWIR) imaging radiometric inspection methods that infer the final material state in LPBF. The instruments’ signals are correlated with bulk and local part properties to evaluate prediction capabilities. A probability framework defines the SWIR camera’s local defect detection successes and limitations. Finally, a superposition thermal model based on SWIR data predicts laser scan path driven thermal history effects for process correction applications”--Abstract, page iv.
","abstract_html":"<p>“Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) fabricates 3D metal parts layer-by-layer. The process enables production of geometrically complex parts that are difficult to inspect with traditional methods. The LPBF parts experience significant geometry driven thermal variations during manufacturing. This creates microstructure and mechanical property inhomogeneities and can stochastically cause defects. Mission critical applications require part qualification by measuring the defects non-destructively. The layer-to-layer nature of LPBF permits non-intrusive measurement of radiometric signals for a part’s entire volume. These measurements provide thermal features that correlate with the local part health. This research establishes Optical Emission Spectroscopy (OES) and Short-Wave Infrared (SWIR) imaging radiometric inspection methods that infer the final material state in LPBF. The instruments’ signals are correlated with bulk and local part properties to evaluate prediction capabilities. A probability framework defines the SWIR camera’s local defect detection successes and limitations. Finally, a superposition thermal model based on SWIR data predicts laser scan path driven thermal history effects for process correction applications”--Abstract, page iv.</p>","abstract_has_math":false,"creators":["Lough, Cody S."],"institution":"Missouri University of Science and Technology","degree_name":"Ph. D. in Mechanical Engineering","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T03:18:09Z","subjects":["Additive Manufacturing","In-Situ Monitoring","Laser Powder Bed Fusion","Thermography","Manufacturing"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsmine.mst.edu/doctoral_dissertations/3133","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Lough, Cody S."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:type","label":"Dc Type","values":["Dissertation - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph. D. in Mechanical Engineering"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Missouri University of Science and Technology"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Additive Manufacturing","In-Situ Monitoring","Laser Powder Bed Fusion","Thermography","Manufacturing"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarsmine.mst.edu/doctoral_dissertations/3133"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["“Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) fabricates 3D metal parts layer-by-layer. The process enables production of geometrically complex parts that are difficult to inspect with traditional methods. The LPBF parts experience significant geometry driven thermal variations during manufacturing. This creates microstructure and mechanical property inhomogeneities and can stochastically cause defects. Mission critical applications require part qualification by measuring the defects non-destructively. The layer-to-layer nature of LPBF permits non-intrusive measurement of radiometric signals for a part’s entire volume. These measurements provide thermal features that correlate with the local part health. This research establishes Optical Emission Spectroscopy (OES) and Short-Wave Infrared (SWIR) imaging radiometric inspection methods that infer the final material state in LPBF. The instruments’ signals are correlated with bulk and local part properties to evaluate prediction capabilities. A probability framework defines the SWIR camera’s local defect detection successes and limitations. Finally, a superposition thermal model based on SWIR data predicts laser scan path driven thermal history effects for process correction applications”--Abstract, page iv.
"]},{"key":"dc:title","label":"Title","values":["Development of in-situ radiometric inspection methods for quality assurance in laser powder bed fusion"]}]}],"canonical_facts":{"dc:creator":["Lough, Cody S."],"dc:description.abstract":["“Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) fabricates 3D metal parts layer-by-layer. The process enables production of geometrically complex parts that are difficult to inspect with traditional methods. The LPBF parts experience significant geometry driven thermal variations during manufacturing. This creates microstructure and mechanical property inhomogeneities and can stochastically cause defects. Mission critical applications require part qualification by measuring the defects non-destructively. The layer-to-layer nature of LPBF permits non-intrusive measurement of radiometric signals for a part’s entire volume. These measurements provide thermal features that correlate with the local part health. This research establishes Optical Emission Spectroscopy (OES) and Short-Wave Infrared (SWIR) imaging radiometric inspection methods that infer the final material state in LPBF. The instruments’ signals are correlated with bulk and local part properties to evaluate prediction capabilities. A probability framework defines the SWIR camera’s local defect detection successes and limitations. Finally, a superposition thermal model based on SWIR data predicts laser scan path driven thermal history effects for process correction applications”--Abstract, page iv.
"],"dc:identifier":["https://scholarsmine.mst.edu/doctoral_dissertations/3133"],"dc:subject":["Additive Manufacturing","In-Situ Monitoring","Laser Powder Bed Fusion","Thermography","Manufacturing"],"dc:title":["Development of in-situ radiometric inspection methods for quality assurance in laser powder bed fusion"],"dc:type":["Dissertation - Open Access"],"thesis:degree_name":["Ph. D. in Mechanical Engineering"],"thesis:institution_name":["Missouri University of Science and Technology"]},"updated_at":"2026-07-24T03:18:09Z"}