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Exploring cutting parameters for enhanced performance in abrasive water jet machining of Al 6061 hybrid nanocomposite
In this study, an investigation was accomplished to optimize the cutting variables of abrasive water jet machining (AWJM) of aluminum (Al) Al 6061 alloy reinforced with 0.6 wt.% silicon carbide (SiC) and 0.2 wt.% boron carbide (B 4 C) hybrid nano metal matrix composite (MMC) using ultrasonic assiste...
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Published in: | Proceedings of the Institution of Mechanical Engineers. Part E, Journal of process mechanical engineering Journal of process mechanical engineering, 2024-12 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | In this study, an investigation was accomplished to optimize the cutting variables of abrasive water jet machining (AWJM) of aluminum (Al) Al 6061 alloy reinforced with 0.6 wt.% silicon carbide (SiC) and 0.2 wt.% boron carbide (B 4 C) hybrid nano metal matrix composite (MMC) using ultrasonic assisted stir casting methodology. The physical, mechanical, and microstructural properties were examined, and the addition of nanoparticles increased the density of the Al 6061 alloy to 2.698 g/cm³. The Vicker's microhardness evaluation showed 63.795 HV, which is 18% higher than the Al 6061 alloy. The metallurgical examination confirmed the even dissemination of SiC and B 4 C nanoparticles. Taguchi's methodology was employed to investigate the impact of a mixture of water and abrasive jet pressure, the nozzle's traverse speed, and the abrasive size on machining attributes such as material removal rate (MRR) and surface roughness. According to the experimental investigations of MRR, the cutting variable that has the greatest impact is jet pressure, which is 72.28%. However, considering the surface roughness, the significant cutting variable is abrasive particle size, which is 74.59%. The cutting wear mechanism was extremely operational in material removal, as evidenced by the high-resolution scanning electron microscope images of the machined surface. |
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ISSN: | 0954-4089 2041-3009 |
DOI: | 10.1177/09544089241301602 |