Sustainability assessment of machining Al 6061-T6 using Taguchi-grey relation integrated approach
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27230%2F24%3A10255770" target="_blank" >RIV/61989100:27230/24:10255770 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.webofscience.com/wos/woscc/full-record/WOS:001269353300001" target="_blank" >https://www.webofscience.com/wos/woscc/full-record/WOS:001269353300001</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.heliyon.2024.e33726" target="_blank" >10.1016/j.heliyon.2024.e33726</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Sustainability assessment of machining Al 6061-T6 using Taguchi-grey relation integrated approach
Popis výsledku v původním jazyce
Modern machining requires reduction in energy usage, surface roughness, and burr width to produce finished or near-finished parts. To ensure high surface quality in machining processes, it is crucial to minimize surface finish and minimize burr width, which are considered as significant parameters as specific cutting energy. The objective of this study was to identify the optimal machining parameters for milling in order to minimize surface roughness, burr width, and specific cutting energy. To achieve this, the research investigated the impact of feed per tooth, cutting speed, depth of cut, and number of inserts on the responses across three intervals using Taguchi L9 array. Observing the responses by varying these parameters, underlined the need for multi objective optimisation. Machining conditions of 0.14 mm/tooth fz, 350 m/min Vc and 2 mm ap using 1 cutting insert (exp no 9) was identified as the best machining run using grey relational analysis owing to its highest grey relational grade of 0.936. ANOVA examination identified cutting speed as the leading factor impacting the grey relational grade with 31.07 % contribution ratio, with the number of inserts, depth of cut, and feed per tooth also making notable contributions. Conclusively, machining parameters identified through response surface optimisation resulted in 21.69 % improvement in surface finish, 11.39 % reduction in specific energy consumption, and 6.2 % decrease in burr width on the down milling side albeit with an increase of 9 % in burr width on the up-milling side.
Název v anglickém jazyce
Sustainability assessment of machining Al 6061-T6 using Taguchi-grey relation integrated approach
Popis výsledku anglicky
Modern machining requires reduction in energy usage, surface roughness, and burr width to produce finished or near-finished parts. To ensure high surface quality in machining processes, it is crucial to minimize surface finish and minimize burr width, which are considered as significant parameters as specific cutting energy. The objective of this study was to identify the optimal machining parameters for milling in order to minimize surface roughness, burr width, and specific cutting energy. To achieve this, the research investigated the impact of feed per tooth, cutting speed, depth of cut, and number of inserts on the responses across three intervals using Taguchi L9 array. Observing the responses by varying these parameters, underlined the need for multi objective optimisation. Machining conditions of 0.14 mm/tooth fz, 350 m/min Vc and 2 mm ap using 1 cutting insert (exp no 9) was identified as the best machining run using grey relational analysis owing to its highest grey relational grade of 0.936. ANOVA examination identified cutting speed as the leading factor impacting the grey relational grade with 31.07 % contribution ratio, with the number of inserts, depth of cut, and feed per tooth also making notable contributions. Conclusively, machining parameters identified through response surface optimisation resulted in 21.69 % improvement in surface finish, 11.39 % reduction in specific energy consumption, and 6.2 % decrease in burr width on the down milling side albeit with an increase of 9 % in burr width on the up-milling side.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20301 - Mechanical engineering
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2024
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Heliyon
ISSN
2405-8440
e-ISSN
2405-8440
Svazek periodika
10
Číslo periodika v rámci svazku
13
Stát vydavatele periodika
GB - Spojené království Velké Británie a Severního Irska
Počet stran výsledku
16
Strana od-do
—
Kód UT WoS článku
001269353300001
EID výsledku v databázi Scopus
2-s2.0-85197566059