Investigation of Surface Roughness and Predictive Modelling of Machining Stellite 6
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23210%2F19%3A43958515" target="_blank" >RIV/49777513:23210/19:43958515 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.mdpi.com/1996-1944/12/16/2551" target="_blank" >https://www.mdpi.com/1996-1944/12/16/2551</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/ma12162551" target="_blank" >10.3390/ma12162551</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Investigation of Surface Roughness and Predictive Modelling of Machining Stellite 6
Popis výsledku v původním jazyce
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 vc (mmin????1), in the case of turning and milling, and the feed rate f (mmrev????1) and the depth of cut ap (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.
Název v anglickém jazyce
Investigation of Surface Roughness and Predictive Modelling of Machining Stellite 6
Popis výsledku anglicky
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 vc (mmin????1), in the case of turning and milling, and the feed rate f (mmrev????1) and the depth of cut ap (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.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20501 - Materials engineering
Návaznosti výsledku
Projekt
<a href="/cs/project/LO1502" target="_blank" >LO1502: Rozvoj Regionálního technologického institutu</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2019
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Materials
ISSN
1996-1944
e-ISSN
—
Svazek periodika
12
Číslo periodika v rámci svazku
16
Stát vydavatele periodika
CH - Švýcarská konfederace
Počet stran výsledku
23
Strana od-do
—
Kód UT WoS článku
000484464800052
EID výsledku v databázi Scopus
2-s2.0-85070565081