Surface Roughness Analysis and Prediction with an Artificial Neural Network Model for Dry Milling of Co–Cr Biomedical Alloys

The aim of this paper is to conduct an experimental study in order to obtain a roughness (Ra) prediction model for dry end-milling (with an AlTiCrSiN PVD-coated tool) of the Co–28Cr–6Mo and Co–20Cr–15W–10Ni biomedical alloys, a model that can contribute to more quickly obtaining the desired surface...

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Autores principales:	Manuela-Roxana Dijmărescu, Bogdan Felician Abaza, Ionelia Voiculescu, Maria-Cristina Dijmărescu, Ion Ciocan
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	roughness prediction biomedical alloys machining Co–28Cr–6Mo Co–20Cr–15W–10Ni ANN model AlTiCrSiN PVD coated tool Technology T Electrical engineering. Electronics. Nuclear engineering TK1-9971 Engineering (General). Civil engineering (General) TA1-2040 Microscopy QH201-278.5 Descriptive and experimental mechanics QC120-168.85
Acceso en línea:	https://doaj.org/article/75d6659a8ab9473fbefcfb52e3cc35c0
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Surface Roughness Analysis and Prediction with an Artificial Neural Network Model for Dry Milling of Co–Cr Biomedical Alloys

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