Speaker: Lacie Feller, Senior Application Engineer, Altair Engineering
Topic: Anomaly Detection in Additive Manufacturing: More Than a 3-Dimensional Problem
ABSTRACT Additive manufacturing has transformed the manufacturing process by allowing us to construct complex shapes, produce custom designs, and reduce tooling requirements. However, there are still many challenges that prevent the widespread adoption of 3D printed processes, including concerns about the consistency and reliability of 3D printed parts. Porosity defects discovered after printing can compromise strength of the design and lead to early failure. Can we develop a machine learning model to flag parts with defects based on sensor data during the build? We’ll look at what goes into model development and the results of modeling efforts so far.
BIOGRAPHY Lacie Feller is a Senior Application Engineer with Altair Engineering. She joined Altair in 2017 and works on structural FEA and data analytics applications. She earned her bachelor’s degree in biomedical engineering from The University of Texas at Austin and master’s degree from University of California, Davis.
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