Predictive Modeling of Vickers Hardness Using Machine Learning Techniques on D2 Steel with Various Treatments

Hardness is one of the most crucial mechanical properties, serving as a key indicator of a material’s suitability for specific applications and its resistance to fracturing or deformation under operational conditions. Machine learning techniques have emerged as valuable tools for swiftly and accurat...

Full description

Autores:
Ortega-Portilla, Carolina
Mambuscay, Claudia Lorena
Piamba Jiménez, Jeferson Fernando
Forero Vargas, Manuel Guillermo
Tipo de recurso:
Article of investigation
Fecha de publicación:
2024
Institución:
Universidad de Ibagué
Repositorio:
Repositorio Universidad de Ibagué
Idioma:
eng
OAI Identifier:
oai:repositorio.unibague.edu.co:20.500.12313/5915
Acceso en línea:
https://doi.org/ 10.3390/ma17102235
https://hdl.handle.net/20.500.12313/5915
https://www.mdpi.com/1996-1944/17/10/2235
Palabra clave:
Dureza Vickers - Modelado predictivo
Acero D2 - Aprendizaje automático
Coating
Indentation imprint
Machine learning
Regression
Titanium Niobium Nitride (TiNbN)
Vickers hardness
Rights
openAccess
License
© 2024 by the authors.