{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/135735"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/135735","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Laser Powder Bed Fusion (LPBF) of a Complex Aerospace Component: Effects of Layerwise Process Control on Part Quality","abstract":"This research concerns the laser powder bed fusion (LPBF) metal additive manufacturing (AM) process. The goal is to optimize critical processing parameters for a complex LPBF part. Currently, LPBF process qualification relies on empirical parameter experiments and rigorous materials characterization. Once applied to end-use, complex geometries, this process can take over 2 years of engineering effort and more than $4 million dollars. Further, empirically-determined process parameters often do not scale to complex parts without expensive supporting structures required to maintain a stable manufacturing process. During the LPBF process, the part is subjected to continual heating and cooling cycles. This thermal history governs every aspect of the part's quality, from its microstructure, defects, geometric accuracy, residual stresses, and ultimately, determines its functional properties. Hence, controlling the thermal history is critical for obtaining high quality LPBF parts. Accordingly, the objective of this work is to evaluate part quality, thermal history, and support structure optimization of process-controlled parts to compare against their nominally printed counterparts. This approach leverages a feedforward thermal history control algorithm known as DynamicPrint for LPBF of a complex aerospace component (GE bracket) made from Inconel 718 material. This approach, which is a form of model predictive feedforward control, uses a physics-based model to autonomously adjust processing parameters layer-by-layer before the part is printed to avoid heat build-up and thermal history excursions during printing. This research tests and affirms the hypothesis that controlling the thermal history via layerwise modulation of laser power and velocity improves part quality. This thesis evaluates and compares the quality of thermal history-controlled LPBF parts against parts printed with empirically optimized, constant process parameters. Compared to uncontrolled parts, process-controlled parts show improved dimensional accuracy and reduced thermal-induced warping. Specifically, compared to parts produced under fixed, nominal conditions, layerwise control eliminated distortion defects and reduced necessary support structure volume by 45%. This work demonstrates a scalable approach for applying layerwise thermal history process control to a complex geometry, where a key challenge in practical LPBF applications lies in dynamically modifying process parameters to accommodate complex geometries. Notably, this method enables rapid, autonomous optimization of process conditions in LPBF – critical to accelerated part qualification – and reduces process development time from months to weeks, while fabricating better quality parts that cost less.","abstract_html":"This research concerns the laser powder bed fusion (LPBF) metal additive manufacturing (AM) process. The goal is to optimize critical processing parameters for a complex LPBF part. Currently, LPBF process qualification relies on empirical parameter experiments and rigorous materials characterization. Once applied to end-use, complex geometries, this process can take over 2 years of engineering effort and more than $4 million dollars. Further, empirically-determined process parameters often do not scale to complex parts without expensive supporting structures required to maintain a stable manufacturing process. During the LPBF process, the part is subjected to continual heating and cooling cycles. This thermal history governs every aspect of the part's quality, from its microstructure, defects, geometric accuracy, residual stresses, and ultimately, determines its functional properties. Hence, controlling the thermal history is critical for obtaining high quality LPBF parts. Accordingly, the objective of this work is to evaluate part quality, thermal history, and support structure optimization of process-controlled parts to compare against their nominally printed counterparts. This approach leverages a feedforward thermal history control algorithm known as DynamicPrint for LPBF of a complex aerospace component (GE bracket) made from Inconel 718 material. This approach, which is a form of model predictive feedforward control, uses a physics-based model to autonomously adjust processing parameters layer-by-layer before the part is printed to avoid heat build-up and thermal history excursions during printing. This research tests and affirms the hypothesis that controlling the thermal history via layerwise modulation of laser power and velocity improves part quality. This thesis evaluates and compares the quality of thermal history-controlled LPBF parts against parts printed with empirically optimized, constant process parameters. Compared to uncontrolled parts, process-controlled parts show improved dimensional accuracy and reduced thermal-induced warping. Specifically, compared to parts produced under fixed, nominal conditions, layerwise control eliminated distortion defects and reduced necessary support structure volume by 45%. This work demonstrates a scalable approach for applying layerwise thermal history process control to a complex geometry, where a key challenge in practical LPBF applications lies in dynamically modifying process parameters to accommodate complex geometries. Notably, this method enables rapid, autonomous optimization of process conditions in LPBF – critical to accelerated part qualification – and reduces process development time from months to weeks, while fabricating better quality parts that cost less.","abstract_has_math":false,"creators":["Spadaccia, David Paul"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Mechanical Engineering","degree_department":"Mechanical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Williams, Christopher Bryant","Rao, Prahalada Krishna"],"committee_members":["West, Robert L."],"year":2025,"date_issued":"2025-06-27","date_published":"2025-06-27","updated_at":"2026-07-22T22:20:34Z","subjects":["Additive Manufacturing","Laser Powder Bed Fusion","Process Control","Topology Optimization"],"languages":["en"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:44209"],"render_values":[{"text":"vt_gsexam:44209","href":null,"code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/10919/135735","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Williams, Christopher Bryant","Rao, Prahalada Krishna"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["West, Robert L."]},{"key":"dc:contributor.department","label":"Department","values":["Mechanical Engineering"]},{"key":"dc:creator","label":"Author","values":["Spadaccia, David Paul"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-06-28T08:00:22Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-06-28T08:00:22Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-06-27"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Additive Manufacturing","Laser Powder Bed Fusion","Process Control","Topology Optimization"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:44209"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10919/135735"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This research concerns the laser powder bed fusion (LPBF) metal additive manufacturing (AM) process. The goal is to optimize critical processing parameters for a complex LPBF part. Currently, LPBF process qualification relies on empirical parameter experiments and rigorous materials characterization. Once applied to end-use, complex geometries, this process can take over 2 years of engineering effort and more than $4 million dollars. Further, empirically-determined process parameters often do not scale to complex parts without expensive supporting structures required to maintain a stable manufacturing process. During the LPBF process, the part is subjected to continual heating and cooling cycles. This thermal history governs every aspect of the part's quality, from its microstructure, defects, geometric accuracy, residual stresses, and ultimately, determines its functional properties. Hence, controlling the thermal history is critical for obtaining high quality LPBF parts. Accordingly, the objective of this work is to evaluate part quality, thermal history, and support structure optimization of process-controlled parts to compare against their nominally printed counterparts. This approach leverages a feedforward thermal history control algorithm known as DynamicPrint for LPBF of a complex aerospace component (GE bracket) made from Inconel 718 material. This approach, which is a form of model predictive feedforward control, uses a physics-based model to autonomously adjust processing parameters layer-by-layer before the part is printed to avoid heat build-up and thermal history excursions during printing. This research tests and affirms the hypothesis that controlling the thermal history via layerwise modulation of laser power and velocity improves part quality. This thesis evaluates and compares the quality of thermal history-controlled LPBF parts against parts printed with empirically optimized, constant process parameters. Compared to uncontrolled parts, process-controlled parts show improved dimensional accuracy and reduced thermal-induced warping. Specifically, compared to parts produced under fixed, nominal conditions, layerwise control eliminated distortion defects and reduced necessary support structure volume by 45%. This work demonstrates a scalable approach for applying layerwise thermal history process control to a complex geometry, where a key challenge in practical LPBF applications lies in dynamically modifying process parameters to accommodate complex geometries. Notably, this method enables rapid, autonomous optimization of process conditions in LPBF – critical to accelerated part qualification – and reduces process development time from months to weeks, while fabricating better quality parts that cost less."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["This research concerns the laser powder bed fusion (LPBF) metal additive manufacturing (AM) process. The goal is to optimize process parameters for a complex LPBF part. Currently, LPBF process qualification for complex parts relies on extensive parameter experiments and rigorous material properties testing. Once applied to end-use, complex geometries, this process can take over 2 years of engineering effort and more than $4 million dollars. Further, experimentally-determined process parameters often do not scale to complex parts without expensive supporting structures required to maintain a stable manufacturing process. During the LPBF process, the part is subjected to continual heating and cooling cycles. This thermal history governs every aspect of the part's quality, from its defects, geometric accuracy, and ultimately determines its functional properties. Hence, controlling thermal history is critical for obtaining high quality LPBF parts. Accordingly, the objective of this work is to evaluate part quality, thermal history, and support structure reduction of process-controlled parts to compare against their nominally printed counterparts. This approach leverages a temperature control algorithm known as DynamicPrint for LPBF of a complex aerospace component (GE bracket) made from Inconel 718 material. This approach uses a physics-based model to autonomously adjust processing parameters layer-by-layer before the part is printed to avoid heat build-up during printing. This research tests and affirms the hypothesis that controlling thermal history through layerwise process parameter changes improve part quality. This thesis evaluates and compares the quality of thermal history-controlled LPBF parts against parts printed with constant process parameters. Compared to uncontrolled parts, process-controlled parts show improved dimensional accuracy and reduced warping associated with overheating. Specifically, compared to parts produced under fixed, nominal conditions, layerwise control eliminated distortion defects and reduced support structure volume by 45%. This work demonstrates a scalable approach for applying layerwise thermal history process control to a complex geometry, where a key challenge in practical LPBF applications lies in modifying process parameters to accommodate complex geometries. Notably, this method enables rapid, autonomous optimization of process conditions in LPBF – critical to accelerated part qualification – and reduces process development time from months to weeks, while fabricating better quality parts that cost less."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Laser Powder Bed Fusion (LPBF) of a Complex Aerospace Component: Effects of Layerwise Process Control on Part Quality"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Williams, Christopher Bryant","Rao, Prahalada Krishna"],"dc:contributor.committeemember":["West, Robert L."],"dc:contributor.department":["Mechanical Engineering"],"dc:creator":["Spadaccia, David Paul"],"dc:date.accessioned":["2025-06-28T08:00:22Z"],"dc:date.available":["2025-06-28T08:00:22Z"],"dc:date.issued":["2025-06-27"],"dc:description.abstract":["This research concerns the laser powder bed fusion (LPBF) metal additive manufacturing (AM) process. The goal is to optimize critical processing parameters for a complex LPBF part. Currently, LPBF process qualification relies on empirical parameter experiments and rigorous materials characterization. Once applied to end-use, complex geometries, this process can take over 2 years of engineering effort and more than $4 million dollars. Further, empirically-determined process parameters often do not scale to complex parts without expensive supporting structures required to maintain a stable manufacturing process. During the LPBF process, the part is subjected to continual heating and cooling cycles. This thermal history governs every aspect of the part's quality, from its microstructure, defects, geometric accuracy, residual stresses, and ultimately, determines its functional properties. Hence, controlling the thermal history is critical for obtaining high quality LPBF parts. Accordingly, the objective of this work is to evaluate part quality, thermal history, and support structure optimization of process-controlled parts to compare against their nominally printed counterparts. This approach leverages a feedforward thermal history control algorithm known as DynamicPrint for LPBF of a complex aerospace component (GE bracket) made from Inconel 718 material. This approach, which is a form of model predictive feedforward control, uses a physics-based model to autonomously adjust processing parameters layer-by-layer before the part is printed to avoid heat build-up and thermal history excursions during printing. This research tests and affirms the hypothesis that controlling the thermal history via layerwise modulation of laser power and velocity improves part quality. This thesis evaluates and compares the quality of thermal history-controlled LPBF parts against parts printed with empirically optimized, constant process parameters. Compared to uncontrolled parts, process-controlled parts show improved dimensional accuracy and reduced thermal-induced warping. Specifically, compared to parts produced under fixed, nominal conditions, layerwise control eliminated distortion defects and reduced necessary support structure volume by 45%. This work demonstrates a scalable approach for applying layerwise thermal history process control to a complex geometry, where a key challenge in practical LPBF applications lies in dynamically modifying process parameters to accommodate complex geometries. Notably, this method enables rapid, autonomous optimization of process conditions in LPBF – critical to accelerated part qualification – and reduces process development time from months to weeks, while fabricating better quality parts that cost less."],"dc:description.abstractgeneral":["This research concerns the laser powder bed fusion (LPBF) metal additive manufacturing (AM) process. The goal is to optimize process parameters for a complex LPBF part. Currently, LPBF process qualification for complex parts relies on extensive parameter experiments and rigorous material properties testing. Once applied to end-use, complex geometries, this process can take over 2 years of engineering effort and more than $4 million dollars. Further, experimentally-determined process parameters often do not scale to complex parts without expensive supporting structures required to maintain a stable manufacturing process. During the LPBF process, the part is subjected to continual heating and cooling cycles. This thermal history governs every aspect of the part's quality, from its defects, geometric accuracy, and ultimately determines its functional properties. Hence, controlling thermal history is critical for obtaining high quality LPBF parts. Accordingly, the objective of this work is to evaluate part quality, thermal history, and support structure reduction of process-controlled parts to compare against their nominally printed counterparts. This approach leverages a temperature control algorithm known as DynamicPrint for LPBF of a complex aerospace component (GE bracket) made from Inconel 718 material. This approach uses a physics-based model to autonomously adjust processing parameters layer-by-layer before the part is printed to avoid heat build-up during printing. This research tests and affirms the hypothesis that controlling thermal history through layerwise process parameter changes improve part quality. This thesis evaluates and compares the quality of thermal history-controlled LPBF parts against parts printed with constant process parameters. Compared to uncontrolled parts, process-controlled parts show improved dimensional accuracy and reduced warping associated with overheating. Specifically, compared to parts produced under fixed, nominal conditions, layerwise control eliminated distortion defects and reduced support structure volume by 45%. This work demonstrates a scalable approach for applying layerwise thermal history process control to a complex geometry, where a key challenge in practical LPBF applications lies in modifying process parameters to accommodate complex geometries. Notably, this method enables rapid, autonomous optimization of process conditions in LPBF – critical to accelerated part qualification – and reduces process development time from months to weeks, while fabricating better quality parts that cost less."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:44209"],"dc:identifier.uri":["https://hdl.handle.net/10919/135735"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Additive Manufacturing","Laser Powder Bed Fusion","Process Control","Topology Optimization"],"dc:title":["Laser Powder Bed Fusion (LPBF) of a Complex Aerospace Component: Effects of Layerwise Process Control on Part Quality"],"dc:type":["Thesis"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:20:34Z"}