Cargando…
Milling of Graphene Reinforced Ti6Al4V Nanocomposites: An Artificial Intelligence Based Industry 4.0 Approach
The studies about the effect of the graphene reinforcement ratio and machining parameters to improve the machining performance of Ti6Al4V alloy are still rare and incomplete to meet the Industry 4.0 manufacturing criteria. In this study, a hybrid adaptive neuro-fuzzy inference system (ANFIS) with a...
Autores principales: | M. Nasr, Mustafa, Anwar, Saqib, M. Al-Samhan, Ali, Ghaleb, Mageed, Dabwan, Abdulmajeed |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7765064/ https://www.ncbi.nlm.nih.gov/pubmed/33327585 http://dx.doi.org/10.3390/ma13245707 |
Ejemplares similares
-
Sustainable Microfabrication Enhancement of Graphene Nanoplatelet-Reinforced Biomedical Alumina Ceramic Matrix Nanocomposites
por: Nasr, Mustafa M., et al.
Publicado: (2023) -
Investigations on the Effect of Layers’ Thickness and Orientations in the Machining of Additively Manufactured Stainless Steel 316L
por: Dabwan, Abdulmajeed, et al.
Publicado: (2021) -
Integrated Intelligent Method Based on Fuzzy Logic for Optimizing Laser Microfabrication Processing of GnPs-Improved Alumina Nanocomposites
por: Alqahtani, Khaled N., et al.
Publicado: (2023) -
A Comprehensive Analysis of the Effect of Graphene-Based Dielectric for Sustainable Electric Discharge Machining of Ti-6Al-4V
por: Ishfaq, Kashif, et al.
Publicado: (2020) -
Graphene nanoparticles as data generating digital materials in industry 4.0
por: Ali, Muhammad A., et al.
Publicado: (2023)