About this Abstract |
Meeting |
2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
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Symposium
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2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
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Presentation Title |
Surface Roughness Measurements of Additively Manufactured Components via X-Ray Computed Tomography |
Author(s) |
Julio C. Ortega Rojas, Amir Ziabari, Obaid Rahman, Paul Brackman, Curtis Frederick, Michael Kirka |
On-Site Speaker (Planned) |
Julio C. Ortega Rojas |
Abstract Scope |
The surface topology and roughness of a material play a crucial role in determining functional properties, impacting aspects such as fluid dynamics, heat transfer, frictional behavior, and mechanical performance. Additive manufacturing (AM) has emerged as a transformative technology, offering unique advantages for fabricating components with complex geometries and novel materials, improving the efficiency of numerous applications. However, a limiting factor of AM is the surface quality of the as-built components, remaining as a critical constraint when good fatigue properties are required for an application. This study focuses on investigating the surface roughness of components fabricated via additive manufacturing. X-Ray computed tomography (CT) data and deep learning algorithms were leveraged to conduct a comprehensive evaluation of surface characteristics and compare our findings with those obtained from confocal microscopy. By exploring the usage of deep learning algorithms, we reveal the potential of advanced CT techniques to evaluate surface roughness of AM components. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |