Chang-Eun Kim1,Clara Druzgalski1,Alexandra Loaiza2,David Bahr2,Gabe Guss1,Vincenzo Lordi1,Patrick Allen1,Rebecca Dylla-Spears1,Manyalibo Matthews1
Lawrence Livermore National Laboratory1,Purdue University2
Chang-Eun Kim1,Clara Druzgalski1,Alexandra Loaiza2,David Bahr2,Gabe Guss1,Vincenzo Lordi1,Patrick Allen1,Rebecca Dylla-Spears1,Manyalibo Matthews1
Lawrence Livermore National Laboratory1,Purdue University2
The laser powder bed fusion process creates a unique microstructure that impacts the property of printed parts. We asked whether the time interval between neighboring meltpool track was a critical parameter that dictates the process--structure relationship. We used metallography, machine learning, and laser toolpath trajectory analyses to collect the data needed to establish a correlation. We found a clear negative correlation between the size of meltpools and the proposed timing descriptor, as `beam crossing interval (BCI)'. The observed correlation paves a way to enable a data-driven model to control the microstructure of metal part printed by the laser powder bed fusion. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344.