@ARTICLE{Bhagwat_Vishal_B._An_2024,
 author={Bhagwat, Vishal B. and Kamble, Dhanpal A. and Kore, Sandeep S.},
 volume={vol. 69},
 number={No 4},
 pages={1577-1584},
 journal={Archives of Metallurgy and Materials},
 howpublished={online},
 year={2024},
 publisher={Institute of Metallurgy and Materials Science of Polish Academy of Sciences},
 publisher={Committee of Materials Engineering and Metallurgy of Polish Academy of Sciences},
 abstract={This paper presents an overview of different machine learning (ML) techniques and algorithms implemented in metal casting industries. ML has made significant contributions to the field of metal casting by improving various aspects of the casting process. In this work, referred quality research papers are divided into two categories. Firstly, work reviewed for the automation in foundry and quality control. Secondly, the raw material melting, material designs and defect predictions in the metal casting. The literature is extensively studied for types of ML models implemented from 2010 to 2023 for the sand-casting application area especially in the prediction of material melting compositions, desired material properties and occurrence of defects along with involvement of advanced foundry technologies.},
 title={An Overview of Machine Learning Applications in Metal Casting Industries},
 type={Article},
 URL={http://journals.pan.pl/Content/133570/AMM-2024-4-38-Bhagwat.pdf},
 doi={10.24425/amm.2024.151428},
 keywords={Metal casting, Machine learning, artificial intelligence, quality control, defects prediction},
}