This github repository contains the datasets and codes for our paper "MeltpoolNet: Melt pool Characteristic Prediction in Metal Additive Manufacturing Using Machine Learning" published in the jounal of Additive Manufacturing.
Two dataset has been collected for the MeltpoolNet:
- Regression dataset for the meltpool geometry
- Classification dataset for the meltpool modes and defects
The following modules and packages are required in order to run the associated code:
- numpy
- pandas
- sklearn
- XGBoost
- matplotlib
- scipy
- hyperopt
They can be installed independently, or all at once by running pip install -r requirements.txt. "requirements.txt" file can be found here.
Our paper can be found here.
If you use our data and notebook please cite:
@article{AKBARI2022102817,
title = {MeltpoolNet: Melt pool characteristic prediction in Metal Additive Manufacturing using machine learning},
journal = {Additive Manufacturing},
volume = {55},
pages = {102817},
year = {2022},
issn = {2214-8604},
doi = {https://doi.org/10.1016/j.addma.2022.102817},
url = {https://www.sciencedirect.com/science/article/pii/S2214860422002172},
author = {Parand Akbari and Francis Ogoke and Ning-Yu Kao and Kazem Meidani and Chun-Yu Yeh and William Lee and Amir {Barati Farimani}}}
Parand Akbari, Francis Ogoke, Ning-Yu Kao, Kazem Meidani, Chun-Yu Yeh, William Lee, Amir Barati Farimani