In this repository, we propose a generalizable ML framework for the prediction of clad geometrical features and optimal process window in Metal Additive Manufacturing. You can check out our paper for more details.
This repository has been tested on the following environemt:
python == 3.10.11
gradio == 3.23.0
scikit-learn == 1.2.2
pandas == 1.5.3
numpy == 1.24.3
matplotlib == 3.7.1
scipy == 1.9.3
Clone the repository in your local machine, and activate your conda environement:
git clone https://github.com/sinatayebati/CladNet-ML-for-AM.git
cd CladNet-ML-for-AM
conda activate env.cladnet
Install the requirements:
pip install -r requirements.txt
if you find our work useful in your research, please consider citing:
@article{tayebati2023hybrid,
title={A hybrid machine learning framework for clad characteristics prediction in metal additive manufacturing},
author={Tayebati, Sina and Cho, Kyu Taek},
journal={arXiv preprint arXiv:2307.01872},
year={2023}
}