作者
Hamed Elwarfalli, Dimitri Papazoglou, Dathan Erdahl, Amy Doll, Jared Speltz
发表日期
2019/7/15
研讨会论文
2019 IEEE National Aerospace and Electronics Conference (NAECON)
页码范围
323-327
出版商
IEEE
简介
Additive Manufacturing (AM) is a growing field for various industries of avionics, biomedical, automotive and manufacturing. The onset of Laser Powder Bed Fusion (LPBF) technologies for metal printing has shown exceptional growth in the past 15 years. Quality of parts for LPBF is a concern for the industry, as many parts produced are high risk, such as biomedical implants. To address these needs, a LPBF machine was designed with in-situ sensors to monitor the build process. Image processing and machine learning algorithms provide an efficient means to take bulk data and assess part quality, validating specific internal geometries and build defects. This research will analyze infrared (IR) images from a Selective Laser Melting (SLM) machine using a Computer Aided Design (CAD) designed part, featuring specific geometries (squares, circles, and triangles) of varying sizes (0.75-3.5 mm) on multiple layers for …
引用总数
2020202120222023202415772
学术搜索中的文章
H Elwarfalli, D Papazoglou, D Erdahl, A Doll, J Speltz - 2019 IEEE National Aerospace and Electronics …, 2019