Prediction of Surface Roughness of an Abrasive Water Jet Cut Using an Artificial Neural Network

The study’s primary purpose was to explore the abrasive water jet (AWJ) cut machinability of stainless steel X5CrNi18-10 (1.4301). The study analyzed the effects of such process parameters as the traverse speed (TS), the depth of cut (DC), and the abrasive mass flow rate (AR) on the surface roughnes...

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Detalles Bibliográficos
Autores principales: Ficko, Mirko, Begic-Hajdarevic, Derzija, Cohodar Husic, Maida, Berus, Lucijano, Cekic, Ahmet, Klancnik, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201306/
https://www.ncbi.nlm.nih.gov/pubmed/34198903
http://dx.doi.org/10.3390/ma14113108

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201306/
https://www.ncbi.nlm.nih.gov/pubmed/34198903
http://dx.doi.org/10.3390/ma14113108

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