Optimizing of machining parameters for hypereutectic aluminium silicon alloys A390 with minimum quantity lubrication in turning using vegetable-based nano fluids
Aluminium alloys are rapidly developing in response to regulatory and industry trends. The automotive industry’s push for lighter, more fuel-efficient vehicles has driven the fast-paced development and adoption of aluminium alloys, which have historically been regarded as the automotive production m...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | en en |
| Published: |
IOP Publishing
2024
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| Subjects: | |
| Online Access: | https://umpir.ump.edu.my/id/eprint/42931/1/Optimizing%20of%20machining%20parameters%20for%20hypereutectic%20aluminium%20silicon%20alloys%20A390.pdf https://umpir.ump.edu.my/id/eprint/42931/7/Optimizing%20of%20machining%20parameters%20for%20hypereutectic%20aluminium.pdf https://umpir.ump.edu.my/id/eprint/42931/ https://doi.org/10.1088/1742-6596/2907/1/012020 |
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| Summary: | Aluminium alloys are rapidly developing in response to regulatory and industry trends. The automotive industry’s push for lighter, more fuel-efficient vehicles has driven the fast-paced development and adoption of aluminium alloys, which have historically been regarded as the automotive production material with the fastest rate of growth. Parts made of aluminium alloys are significantly lighter than those made of steel, which can improve fuel efficiency and reduce emissions, making aluminium an environmentally friendly choice. The high silicon concentration in aluminium silicon alloys A390, which varies from 17 to 18% and has good casting qualities, affects the machinability process. In order to optimise machining settings and determine the aspects that most effect surface roughness, this study looks at the machinability performance, concentrating on the surface roughness of machined surfaces. The cutting parameters employed in this study were a constant depth of cut of 0.1 mm, a feed rate of 0.1 to 0.3 mm/min, and a cutting speed range of 300 to 900 m/min. The turning machining process was performed utilising nano-based silicon dioxide (SiO2)-based fluids combined with palm oil as a lubricant under minimal quantity lubricant (MQL) conditions. Next, a mathematical model was developed to predict outcomes, optimize processes, understand variable relationships, and save time and resources. The effect of machining parameters on surface roughness was investigated using the analysis of variance (ANOVA). The ANOVA revealed that feed rate and speed were important factors. The best settings for minimum quantity lubrication (MQL) were 900 m/min for the cutting speed and 0.1 mm/min for the feed rate. With these settings, 0.451 μm of minimised surface roughness was attained. |
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