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Influence of the Tool Cutting Edge Helix Angle on the Surface Roughness after Finish Milling of Magnesium Alloys
This paper shows the surface quality results after finishing milling of AZ91D and AZ31 magnesium alloys. The study was performed for variable technological parameters: cutting speed, feed per tooth, axial depth of cut and radial depth of cut. The tools used in the study were two carbide cutters with...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9100010/ https://www.ncbi.nlm.nih.gov/pubmed/35591519 http://dx.doi.org/10.3390/ma15093184 |
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author | Zagórski, Ireneusz Szczepaniak, Anna Kulisz, Monika Korpysa, Jarosław |
author_facet | Zagórski, Ireneusz Szczepaniak, Anna Kulisz, Monika Korpysa, Jarosław |
author_sort | Zagórski, Ireneusz |
collection | PubMed |
description | This paper shows the surface quality results after finishing milling of AZ91D and AZ31 magnesium alloys. The study was performed for variable technological parameters: cutting speed, feed per tooth, axial depth of cut and radial depth of cut. The tools used in the study were two carbide cutters with a different tool cutting edge helix angle. The measurement of the research results presented the surface roughness parameters was made on the lateral faces and the end faces of the specimens. Statistical analysis and simulations using artificial neural networks were carried out with the Statistica software. The normality of the distribution was examined, and the hypotheses of the equality of mean values and variance were verified. For the AZ91D magnesium alloy on the lateral and the end faces (Ra, Rz parameters), simulations were carried out. Two types of ANN were used: MLP (Multi-layered perceptron) and RBF (Radial Basis Function). To increase the machining stability and to obtain a high surface finish, the more suitable tool for finishing milling is the tool with a helix angle of λ(s) = 20°. Artificial neural networks have been shown to be a good tool for predicting surface roughness parameters of magnesium alloys after finishing milling. |
format | Online Article Text |
id | pubmed-9100010 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91000102022-05-14 Influence of the Tool Cutting Edge Helix Angle on the Surface Roughness after Finish Milling of Magnesium Alloys Zagórski, Ireneusz Szczepaniak, Anna Kulisz, Monika Korpysa, Jarosław Materials (Basel) Article This paper shows the surface quality results after finishing milling of AZ91D and AZ31 magnesium alloys. The study was performed for variable technological parameters: cutting speed, feed per tooth, axial depth of cut and radial depth of cut. The tools used in the study were two carbide cutters with a different tool cutting edge helix angle. The measurement of the research results presented the surface roughness parameters was made on the lateral faces and the end faces of the specimens. Statistical analysis and simulations using artificial neural networks were carried out with the Statistica software. The normality of the distribution was examined, and the hypotheses of the equality of mean values and variance were verified. For the AZ91D magnesium alloy on the lateral and the end faces (Ra, Rz parameters), simulations were carried out. Two types of ANN were used: MLP (Multi-layered perceptron) and RBF (Radial Basis Function). To increase the machining stability and to obtain a high surface finish, the more suitable tool for finishing milling is the tool with a helix angle of λ(s) = 20°. Artificial neural networks have been shown to be a good tool for predicting surface roughness parameters of magnesium alloys after finishing milling. MDPI 2022-04-28 /pmc/articles/PMC9100010/ /pubmed/35591519 http://dx.doi.org/10.3390/ma15093184 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zagórski, Ireneusz Szczepaniak, Anna Kulisz, Monika Korpysa, Jarosław Influence of the Tool Cutting Edge Helix Angle on the Surface Roughness after Finish Milling of Magnesium Alloys |
title | Influence of the Tool Cutting Edge Helix Angle on the Surface Roughness after Finish Milling of Magnesium Alloys |
title_full | Influence of the Tool Cutting Edge Helix Angle on the Surface Roughness after Finish Milling of Magnesium Alloys |
title_fullStr | Influence of the Tool Cutting Edge Helix Angle on the Surface Roughness after Finish Milling of Magnesium Alloys |
title_full_unstemmed | Influence of the Tool Cutting Edge Helix Angle on the Surface Roughness after Finish Milling of Magnesium Alloys |
title_short | Influence of the Tool Cutting Edge Helix Angle on the Surface Roughness after Finish Milling of Magnesium Alloys |
title_sort | influence of the tool cutting edge helix angle on the surface roughness after finish milling of magnesium alloys |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9100010/ https://www.ncbi.nlm.nih.gov/pubmed/35591519 http://dx.doi.org/10.3390/ma15093184 |
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