Influence of MoS2 based nanofluid-MQL on tribological and machining characteristics in turning of AA 2024 T3 aluminum alloy

Yücel, Ayşegül and Yıldırım, Çağrı Vakkas and Sarıkaya, Murat and Şirin, Şenol and Kıvak, Turgay and Gupta, Munish Kumar and Tomaz, Ítalo V. (2021) Influence of MoS2 based nanofluid-MQL on tribological and machining characteristics in turning of AA 2024 T3 aluminum alloy. Journal of Materials Research and Technology, 15. pp. 1688-1704. ISSN 2238-7854

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Abstract

Aluminum (Al) alloys are of particular importance to the aerospace industry owing to the combination of characteristics including strength, ductility, toughness, fatigue life and oxidation resistance as a light metal. This is the case of AA 2024 T3 Al alloy. In particular, machining of these alloys has similar importance for productivity and part quality. Recently, the use of nanofluids, which have various advantages in terms of both cooling ability and tribological aspects, has become popular for the efficient machining of such alloys. In this context, guiding data are needed that enable industry and researchers to machine these types of alloys with high efficiency. Taking these into account, in this study, AA 2024 T3 Al alloy was machined and various machinability indicators such as surface roughness, surface topography, maximum temperature and dominant tool wear mechanism under different cooling/lubrication strategies i.e., dry cutting, base fluid minimum quantity lubrication (MQL) and mineral oil based MoS2 nanofluid MQL (NFMQL) were investigated. As a results, significant improvements have been achieved in surface roughness, surface topography, and maximum temperature with help of NFMQL application. The intensive built-up edge (BUE) and built-up layer (BUL) formations are produced on the cutting tool when machining AA 2024 T3 Al alloy under dry cutting. On the other hand, BUE formation has been significantly eliminated thanks to NFMQL. Moreover, a less damaged cutting edge was obtained when machining Al alloy under NFMQL compared to both dry cutting and MQL environments.

Item Type:	Article
Additional Information:	Funding Information: The authors would like to thank the Erciyes University Research Fund for their financial support of present work (FYL-2020-10160). Publisher Copyright: © 2021 The Author(s)
Uncontrolled Keywords:	/dk/atira/pure/subjectarea/asjc/2500/2503
Departments or Groups:
Depositing User:	Admin SSL
Date Deposited:	19 Oct 2022 23:11
Last Modified:	14 Aug 2023 19:30
URI:	http://repository-testing.wit.ie/id/eprint/4592

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