Advances in additive manufacturing over the past decade have led to applications in multiple fields. In particular, additive manufacturing answers the need for high flexibility in designing complex structures, however, the rapid thermal fluctuations during processing lead to numerous defects and processing-induced residual stresses. In this research, an in-situ approach using Digital Image Correlation (DIC) is developed to monitor the deformation during the processing, and thereby analyze the formation of defects and residual stresses. DIC is a visual technique that compares the changes in speckle pattern in consecutive images of a specimen to determine the displacements and strains. This research aims to utilize the novel in-situ approach to investigate the processing-induced deformations due to variations in two process parameters: layer resolution and print temperature. Preliminary results show how defects like warping and missing material caused strain to decrease. Followed by strain evolution for specimens with different thicknesses which revealed maximum strain for the thinnest specimen. Finally, temperature evolution was observed for each layer and compared to with previous layer temperature for all the combinations of thickness and temperature. Current results are for a PLA specimen with pre-printed speckles. In the future, these concepts can be applied to composite printing to understand the evolution of defects such as voids and delamination during processing.
","abstract_html":"<p>Advances in additive manufacturing over the past decade have led to applications in multiple fields. In particular, additive manufacturing answers the need for high flexibility in designing complex structures, however, the rapid thermal fluctuations during processing lead to numerous defects and processing-induced residual stresses. In this research, an in-situ approach using Digital Image Correlation (DIC) is developed to monitor the deformation during the processing, and thereby analyze the formation of defects and residual stresses. DIC is a visual technique that compares the changes in speckle pattern in consecutive images of a specimen to determine the displacements and strains. This research aims to utilize the novel in-situ approach to investigate the processing-induced deformations due to variations in two process parameters: layer resolution and print temperature. Preliminary results show how defects like warping and missing material caused strain to decrease. Followed by strain evolution for specimens with different thicknesses which revealed maximum strain for the thinnest specimen. Finally, temperature evolution was observed for each layer and compared to with previous layer temperature for all the combinations of thickness and temperature. Current results are for a PLA specimen with pre-printed speckles. In the future, these concepts can be applied to composite printing to understand the evolution of defects such as voids and delamination during processing.</p>","abstract_has_math":false,"creators":["Jani, Martina"],"institution":null,"degree_name":"Master of Aerospace Engineering","degree_level":"Thesis - Open Access","degree_discipline":"College of Engineering","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-12-16T08:00:00Z","date_published":"2021-12-16T08:00:00Z","updated_at":"2026-07-27T19:25:16Z","subjects":["Additive Manufacturing","In-situ","Digital Image Correlation","Temperature Gradients","Polylactic Acid","Structures and Materials"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/edt/641","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Jani, Martina"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["College of Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Aerospace Engineering"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Additive Manufacturing","In-situ","Digital Image Correlation","Temperature Gradients","Polylactic Acid","Structures and Materials"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/edt/641"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Advances in additive manufacturing over the past decade have led to applications in multiple fields. In particular, additive manufacturing answers the need for high flexibility in designing complex structures, however, the rapid thermal fluctuations during processing lead to numerous defects and processing-induced residual stresses. In this research, an in-situ approach using Digital Image Correlation (DIC) is developed to monitor the deformation during the processing, and thereby analyze the formation of defects and residual stresses. DIC is a visual technique that compares the changes in speckle pattern in consecutive images of a specimen to determine the displacements and strains. This research aims to utilize the novel in-situ approach to investigate the processing-induced deformations due to variations in two process parameters: layer resolution and print temperature. Preliminary results show how defects like warping and missing material caused strain to decrease. Followed by strain evolution for specimens with different thicknesses which revealed maximum strain for the thinnest specimen. Finally, temperature evolution was observed for each layer and compared to with previous layer temperature for all the combinations of thickness and temperature. Current results are for a PLA specimen with pre-printed speckles. In the future, these concepts can be applied to composite printing to understand the evolution of defects such as voids and delamination during processing.
"]},{"key":"dc:title","label":"Title","values":["In-Situ Monitoring of Additive Manufacturing Using Digital Image Correlation"]}]}],"canonical_facts":{"dc:creator":["Jani, Martina"],"dc:description.abstract":["Advances in additive manufacturing over the past decade have led to applications in multiple fields. In particular, additive manufacturing answers the need for high flexibility in designing complex structures, however, the rapid thermal fluctuations during processing lead to numerous defects and processing-induced residual stresses. In this research, an in-situ approach using Digital Image Correlation (DIC) is developed to monitor the deformation during the processing, and thereby analyze the formation of defects and residual stresses. DIC is a visual technique that compares the changes in speckle pattern in consecutive images of a specimen to determine the displacements and strains. This research aims to utilize the novel in-situ approach to investigate the processing-induced deformations due to variations in two process parameters: layer resolution and print temperature. Preliminary results show how defects like warping and missing material caused strain to decrease. Followed by strain evolution for specimens with different thicknesses which revealed maximum strain for the thinnest specimen. Finally, temperature evolution was observed for each layer and compared to with previous layer temperature for all the combinations of thickness and temperature. Current results are for a PLA specimen with pre-printed speckles. In the future, these concepts can be applied to composite printing to understand the evolution of defects such as voids and delamination during processing.
"],"dc:identifier":["https://commons.erau.edu/edt/641"],"dc:subject":["Additive Manufacturing","In-situ","Digital Image Correlation","Temperature Gradients","Polylactic Acid","Structures and Materials"],"dc:title":["In-Situ Monitoring of Additive Manufacturing Using Digital Image Correlation"],"thesis:degree_discipline":["College of Engineering"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Aerospace Engineering"]},"updated_at":"2026-07-27T19:25:16Z"}