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Investigation of Surface Roughness and Predictive Modelling of Machining Stellite 6
The aim of the paper was to examine the influence of cutting conditions on the roughness of surfaces machined by longitudinal turning, namely of surfaces coated with Stellite 6 prepared by high-velocity oxygen fuel (HVOF) technology and applied onto a standard structural steel substrate. From the re...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6720876/ https://www.ncbi.nlm.nih.gov/pubmed/31405119 http://dx.doi.org/10.3390/ma12162551 |
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author | Valíček, Jan Řehoř, Jan Harničárová, Marta Gombár, Miroslav Kušnerová, Milena Fulemová, Jaroslava Vagaská, Alena |
author_facet | Valíček, Jan Řehoř, Jan Harničárová, Marta Gombár, Miroslav Kušnerová, Milena Fulemová, Jaroslava Vagaská, Alena |
author_sort | Valíček, Jan |
collection | PubMed |
description | The aim of the paper was to examine the influence of cutting conditions on the roughness of surfaces machined by longitudinal turning, namely of surfaces coated with Stellite 6 prepared by high-velocity oxygen fuel (HVOF) technology and applied onto a standard structural steel substrate. From the results of measurements of the cutting parameters, a prediction model of the roughness parameters was created using mathematical and statistical methods. Based on a more detailed analysis and data comparison, a new method for prediction of parameters of longitudinal turning technology was obtained. The main aim of the paper was to identify the mutual discrete relationships between the substrate roughness and the machining parameters. These were the feed rate v(c) (m·min(−1)), in the case of turning and milling, and the feed rate f (mm·rev(−1)) and the depth of cut a(p) (mm). The paper compared and verified two approaches of this method, namely the mathematical statistical approach, the analytical approach and measured dates. From the evaluated and interpreted results, new equations were formulated, enabling prediction of the material parameters of the workpiece, the technological parameters and the parameters of surface quality. |
format | Online Article Text |
id | pubmed-6720876 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-67208762019-09-10 Investigation of Surface Roughness and Predictive Modelling of Machining Stellite 6 Valíček, Jan Řehoř, Jan Harničárová, Marta Gombár, Miroslav Kušnerová, Milena Fulemová, Jaroslava Vagaská, Alena Materials (Basel) Article The aim of the paper was to examine the influence of cutting conditions on the roughness of surfaces machined by longitudinal turning, namely of surfaces coated with Stellite 6 prepared by high-velocity oxygen fuel (HVOF) technology and applied onto a standard structural steel substrate. From the results of measurements of the cutting parameters, a prediction model of the roughness parameters was created using mathematical and statistical methods. Based on a more detailed analysis and data comparison, a new method for prediction of parameters of longitudinal turning technology was obtained. The main aim of the paper was to identify the mutual discrete relationships between the substrate roughness and the machining parameters. These were the feed rate v(c) (m·min(−1)), in the case of turning and milling, and the feed rate f (mm·rev(−1)) and the depth of cut a(p) (mm). The paper compared and verified two approaches of this method, namely the mathematical statistical approach, the analytical approach and measured dates. From the evaluated and interpreted results, new equations were formulated, enabling prediction of the material parameters of the workpiece, the technological parameters and the parameters of surface quality. MDPI 2019-08-10 /pmc/articles/PMC6720876/ /pubmed/31405119 http://dx.doi.org/10.3390/ma12162551 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 Valíček, Jan Řehoř, Jan Harničárová, Marta Gombár, Miroslav Kušnerová, Milena Fulemová, Jaroslava Vagaská, Alena Investigation of Surface Roughness and Predictive Modelling of Machining Stellite 6 |
title | Investigation of Surface Roughness and Predictive Modelling of Machining Stellite 6 |
title_full | Investigation of Surface Roughness and Predictive Modelling of Machining Stellite 6 |
title_fullStr | Investigation of Surface Roughness and Predictive Modelling of Machining Stellite 6 |
title_full_unstemmed | Investigation of Surface Roughness and Predictive Modelling of Machining Stellite 6 |
title_short | Investigation of Surface Roughness and Predictive Modelling of Machining Stellite 6 |
title_sort | investigation of surface roughness and predictive modelling of machining stellite 6 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6720876/ https://www.ncbi.nlm.nih.gov/pubmed/31405119 http://dx.doi.org/10.3390/ma12162551 |
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