CladNet-ML-for-AM

A hybrid machine learning framework for clad characteristics prediction in metal additive manufacturing

Introduction

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.

Setup and Requirements

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

Cite

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}
}

Authors

Sina Tayebati, Kyu Taek Cho