About this Abstract |
Meeting |
2021 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2021)
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Symposium
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Special Session
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Presentation Title |
Porosity Analysis of Laser Powder Bed Fusion Parts Using the Statistics of Extremes |
Author(s) |
Mahya Shahabi, Anthony D. Rollett, Sneha Prabha Narra |
On-Site Speaker (Planned) |
Mahya Shahabi |
Abstract Scope |
Quality assessment of additively manufactured parts is crucial for industrial adoption of additive manufacturing for fatigue-critical components in the aerospace sector. Current quality assessment methods for additively manufactured parts include the addition of witness specimens to the build and the use of expensive and time-consuming characterization and testing procedures. Not only the “fitness-for-purpose” remains unknown while investigating witness specimens, but also fatigue testing and 3D characterization techniques such as computed tomography are expensive and time-consuming. In this study, we propose using a sub-section of the samples to predict the largest pore size within the sample by applying statistics of extremes on cross-sectional porosity data. Results from this work demonstrate that the model precision depends on the volume of interest and the defect density. There are potential opportunities to extend this quality assessment method to both 3D porosity data and complex geometries. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |