About this Abstract |
Meeting |
1st World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
|
Symposium
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First World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
|
Presentation Title |
Effect of Interlayer Delay Time on the Melt Pool Dimensions in Direct Energy Deposition Process using Machine Learning Techniques |
Author(s) |
Rajib Halder, Anthony D. Rollett, Amit K. Verma, Zhening Yang, Ali Guzel, Anthony D. Rollett |
On-Site Speaker (Planned) |
Rajib Halder |
Abstract Scope |
Ti-6Al-4V is a high-performance two-phase (a + B) alloy, where properties strongly depend on the microstructure of the as-printed parts. Since microstructure is defined by the cooling rate, which also correlates with the melt pool dimensions, it becomes important to study the correlation between the melt pool dimensions and the cooling rate as a function of process parameters for the desired microstructure and geometry. In this study, we used the Random Forest (RF) algorithm to predict the final bead dimensions and established a correlation between the heat accumulation with interlayer delay time during the build. The process-microstructure-property relationships were investigated using both, Canonical Correlation Analysis and RF algorithm. |
Proceedings Inclusion? |
Undecided |