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Research and Method of Roughness Prediction of a Curvilinear Surface after Titanium Alloy Turning

This paper deals with the optimization of process parameters (such as cutting speed and feed rate) to minimize surface roughness in the turning of a titanium alloy (Ti-6Al-4V) workpiece with spherical shape. In the first part of the article, based on the results analysis, a mathematical model is dev...

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Detalles Bibliográficos
Autores principales: Matras, Andrzej, Zębala, Wojciech, Machno, Magdalena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6385030/
https://www.ncbi.nlm.nih.gov/pubmed/30736382
http://dx.doi.org/10.3390/ma12030502
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author Matras, Andrzej
Zębala, Wojciech
Machno, Magdalena
author_facet Matras, Andrzej
Zębala, Wojciech
Machno, Magdalena
author_sort Matras, Andrzej
collection PubMed
description This paper deals with the optimization of process parameters (such as cutting speed and feed rate) to minimize surface roughness in the turning of a titanium alloy (Ti-6Al-4V) workpiece with spherical shape. In the first part of the article, based on the results analysis, a mathematical model is developed. It is shown that cutting speed has little effect on the surface roughness. The second part of the paper presents the application of the developed method to optimize cutting data such as feed rate in order to obtain the surface roughness parameters Ra and Rz of the curvilinear surface of the titanium alloy workpiece at acceptable and aligned, values regardless of the surface shape and its tilted angle. A case study verifies the correctness of the proposed method. The machining time was substantially shortened in comparison to the non-optimized cutting process.
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spelling pubmed-63850302019-02-23 Research and Method of Roughness Prediction of a Curvilinear Surface after Titanium Alloy Turning Matras, Andrzej Zębala, Wojciech Machno, Magdalena Materials (Basel) Article This paper deals with the optimization of process parameters (such as cutting speed and feed rate) to minimize surface roughness in the turning of a titanium alloy (Ti-6Al-4V) workpiece with spherical shape. In the first part of the article, based on the results analysis, a mathematical model is developed. It is shown that cutting speed has little effect on the surface roughness. The second part of the paper presents the application of the developed method to optimize cutting data such as feed rate in order to obtain the surface roughness parameters Ra and Rz of the curvilinear surface of the titanium alloy workpiece at acceptable and aligned, values regardless of the surface shape and its tilted angle. A case study verifies the correctness of the proposed method. The machining time was substantially shortened in comparison to the non-optimized cutting process. MDPI 2019-02-06 /pmc/articles/PMC6385030/ /pubmed/30736382 http://dx.doi.org/10.3390/ma12030502 Text en © 2019 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Matras, Andrzej
Zębala, Wojciech
Machno, Magdalena
Research and Method of Roughness Prediction of a Curvilinear Surface after Titanium Alloy Turning
title Research and Method of Roughness Prediction of a Curvilinear Surface after Titanium Alloy Turning
title_full Research and Method of Roughness Prediction of a Curvilinear Surface after Titanium Alloy Turning
title_fullStr Research and Method of Roughness Prediction of a Curvilinear Surface after Titanium Alloy Turning
title_full_unstemmed Research and Method of Roughness Prediction of a Curvilinear Surface after Titanium Alloy Turning
title_short Research and Method of Roughness Prediction of a Curvilinear Surface after Titanium Alloy Turning
title_sort research and method of roughness prediction of a curvilinear surface after titanium alloy turning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6385030/
https://www.ncbi.nlm.nih.gov/pubmed/30736382
http://dx.doi.org/10.3390/ma12030502
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