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Fabrication and Machinability Study of Al2219 Metal Matrix Composites Reinforced with SiN/MoS2 Nanoparticles Sri Sairam Engineering College

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Kannan, Vetri Velmurugan, author.
Contributor:
Babu, Aditya
Kannan, Venkatesan
Seth, Akshay
Sood, Navya
Sundararajan, Devendiran
Conference Name:
International Conference on Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility (2019-10-11 : Chennai, India)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2019
Summary:
Composites materials are substituting constituents for traditional materials due to their remarkable properties, and the addition of nanoparticles gives a new development in the material domain. The nanoparticles influence on fabrication and machinability investigation study is essential as the composites to be used in applications like automotive and aerospace. The current study investigates the machinability characteristics of Al2219 based metal composites reinforced with nanoparticles of SiN/MoS2. Al2219- reinforcements (SiN and MoS2) composites are fabricated by the method of stir casting. Four different compositions (Al2219/SiN (2 wt% and 4 wt%), , Al2219/2 wt.% SiN/ 2 wt.% MoS2, Al2219/2 wt.% MoS2) are fabricated by varying the different weight percentages of nanoparticles reinforcements. An attempt is made to study the investigation analysis of force, surface roughness, and tool wear using CNC machine lathe to consider the effect of cutting speed, cutting depth, and samples. The machinability test is carried out, and the performance is compared. Addition of 2 wt% of SiN in Al2219 is to increase the hardness of nearly about 21%, 14%, 40% compared to that of other composites. The presence of SiN is found to increase the force, surface roughness, and tool wear. The reinforcement percentage is the most controlling factor for machinability characteristics within the limited range of parameters. Regression models for machining responses are developed, which models show a good agreement between predicted and experimental data. The developed composites found an important product application of industrial and domestic applications
Notes:
Vendor supplied data
Publisher Number:
2019-28-0170
Access Restriction:
Restricted for use by site license

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