Using Design of Experiments in Finite Element Modeling to Identify Critical Variables for Laser Powder Bed Fusion

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Ma, Li
Fong, Jeffrey
Lane, Brandon
Moylan, Shawn
Filliben, James
Heckert, Alan
Levine, Lyle

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University of Texas at Austin


Input of accurate material and simulation parameters is critical for accurate predictions in Laser Powder Bed Fusion (L-PBF) Finite Element Analysis (FEA). It is challenging and resource consuming to run experiments that measure and control all possible material properties and process parameters. In this research, we developed a 3-dimensional thermal L-PBF FEA model for a single track laser scan on one layer of metal powder above a solid metal substrate. We applied a design of experiments (DOE) approach which varies simulation parameters to identify critical variables in L-PBF. DOE is an exploratory tool for examining a large number of factors and alternative modeling approaches. It also determines which approaches can best predict L-PBF process performance.


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