Investigation on tribological performance of CuO vegetable-oil based nanofluids for grinding operations

doi:10.1007/s40436-020-00314-1

Abstract

Abstract: With ball-bearing and tribofilm lubrication effects, CuO vegetable oil-based nanofluids have exhibited excellent anti-wear and friction reduction properties. In this study, CuO nanofluids were synthesized by a one-step electro discharge process in distilled water containing polysorbate-20 and vegetable oil as a nanoparticle stabilizer and source of fatty-acid molecules in the base fluid, respectively. Pin-on-disk tribotests were conducted to evaluate the lubrication performance of synthesized CuO nanofluids between brass/steel contact pairs under various loadings. Surface grinding experiments under minimum lubrication conditions were also performed to evaluate the effectiveness of the synthesized nanofluids in improving the machining characteristics and surface quality of machined parts. The results of pin-on-disk tests revealed that adding nanofluids containing 0.5% and 1% (mass fraction) CuO nanoparticles to the base fluid reduced the wear rate by 66.7% and 71.2%, respectively, compared with pure lubricant. The lubricating action of 1% (mass fraction) CuO nanofluid reduced the ground surface roughness by up to 30% compared with grinding using lubricant without nano-additives. These effects were attributed to the formation of a lubrication film between the contact pairs, providing the rolling and healing functions of CuO nanoparticles to the sliding surfaces. The micrography of ground surfaces using a scanning electron microscope confirmed the tribological observations.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00314-1

Key words: CuO nanofluids, Tribology, Lubrication, Wear, Coefficient of friction, Surface roughness

Mirsadegh Seyedzavvar, Hossein Abbasi, Mehdi Kiyasatfar, Reza Najati Ilkhchi. Investigation on tribological performance of CuO vegetable-oil based nanofluids for grinding operations[J]. Advances in Manufacturing, 2020, 8(3): 344-360.

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URL: https://www.aim.shu.edu.cn/EN/10.1007/s40436-020-00314-1

https://www.aim.shu.edu.cn/EN/Y2020/V8/I3/344

References

1. Li BH, Lin Z, Lei R et al (2011) Further discussion on cloud manufacturing. Comput Integr Manuf Syst 17(3):449-457
2. Li B, Zhang L, Chai X (2010) Introduction to cloud manufacturing. ZTE. Communications 8(4):6-9
3. Golightly D, Sharples S, Patel H et al (2016) Manufacturing in the cloud:a human factors perspective. Int J Ind Ergon 55:12-21
4. He W, Xu L (2015) A state-of-the-art survey of cloud manufacturing. Int J Comput Integr Manuf 28(3):239-250
5. Jiang YX, Zhang Y, Ma JW (2013) Research on virtualization of manufacturing resources. In:Proceedings of 2013 2nd international conference on measurement, information and control, vol 2, pp 1060-1064. IEEE
6. Ren L, Cui J, Li N et al (2015) Cloud-based intelligent user interface for cloud manufacturing:model, technology, and application. J Manuf Sci Eng 137(4):040910
7. Ma CX, Ren L, Teng DX et al (2011) Ubiquitous human-computer interaction in cloud manufacturing. Comput Integr Manuf Syst 17(3):504-510
8. Wei Y, Blake MB (2010) Service-oriented computing and cloud computing:challenges and opportunities. IEEE Internet Comput 14(6):72-75
9. Singh B, Dhawan S, Arora A et al (2013) A view of cloud computing. Int J Comput Technol 4(2b1):50-58
10. Ding B, Yu XY, Sun LJ (2012) A cloud-based collaborative manufacturing resource sharing services. Inf Technol J 11(9):1258-1264
11. Ren L, Zhang L, Wang L et al (2017) Cloud manufacturing:key characteristics and applications. Int J Comput Integr Manuf 30(6):501-515
12. Katzmaier A, Hanneghan M (2013) Design pattern evaluation of mobile and web based application frameworks. In:International conference on developments in esystems engineering, pp 157-162. IEEE Computer Society
13. Zhang L, Luo YL, Fan WH et al (2011) Analyses of cloud manufacturing and related advanced manufacturing models. Comput Integr Manuf Syst 17(3):458-468
14. Fei T, Lin Z, Hua G et al (2011) Typical characteristics of cloud manufacturing and several key issues of cloud service composition. Comput Integr Manuf Syst 17(3):477-486
15. Yin C, Huang BQ, Liu F et al (2011) Common key technology system of cloud manufacturing service platform for small and medium enterprises. Comput Integr Manuf Syst 17(3):495-503
16. Gu P, Hashemian M, Nee AYC (2004) Adaptable design. CIRP Ann Manuf Technol 53(2):539-557
17. Tao F, Laili YJ, Xu LD et al (2013) FC-PACO-RM:a parallel method for service composition optimal-selection in cloud manufacturing system. IEEE Trans Ind Inf 9(4):2023-2033
18. Xu X (2012) From cloud computing to cloud manufacturing. Robot Comput Integr Manuf 28(1):75-86
19. Ren L, Zhang L, Zhang YB et al (2011) Resource virtualization in cloud manufacturing. Comput Integr Manuf Syst 17(3):511-518
20. Wang W, Liu F (2012) The research of cloud manufacturing resource discovery mechanism. In:2012 7th international conference on computer science & education (ICCSE), pp 188-191. IEEE
21. Tao F, Zhang L, Venkatesh VC et al (2011) Cloud manufacturing:a computing and service-oriented manufacturing model. J Eng Manuf 225(10):1969-1976
22. Tao F, Zuo Y, Xu LD et al (2014) IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. IEEE Trans Ind Inf 10(2):1547-1557
23. Burkett WC (2001) Product data markup language:a new paradigm for product data exchange and integration. Comput Aided Des 33(7):489-500
24. Srinivasan N, Paolucci M, Sycara K (2006) Semantic web service discovery in the OWL-S IDE. In:Proceedings of the 39th annual Hawaii international conference on system sciences (HICSS'06), vol 6, pp 109b-109b. IEEE
25. Felfernig A, Friedrich GE, Jannach D (2000) UML as domain specific language for the construction of knowledge-based configuration systems. Int J Softw Eng Knowl Eng 10(4):449-469
26. Liu N, Li X, Wang Q (2011) A resource and capability virtualization method for cloud manufacturing systems. In:2011 IEEE international conference on systems, man, and cybernetics, pp 1003-1008. IEEE
27. Wei W, Liang H, Xu SP (2015) Module division method of robust product platform based on improved artificial immune algorithms. Comput Integr Manuf Syst 21(4):885-893
28. Shuping YI, Tan M, Guo Z et al (2015) Manufacturing task decomposition optimization in cloud manufacturing service platform. Comput Integr Manuf Syst 21(8):2201-2212
29. Yip AL, Corney JR, Jagadeesan AP et al (2013) A product configurator for cloud manufacturing. In:ASME 2013 international manufacturing science and engineering conference collocated with the 41st North American manufacturing research conference, June 10-14, Madison, Wisconsin, USA
30. Li BH, Zhang L, Wang SL et al (2010) Cloud manufacturing:a new service-oriented networked manufacturing model. Comput Integr Manuf Syst 16(1):1-7
31. Wang L, Keshavarzmanesh S, Feng HY et al (2009) Assembly process planning and its future in collaborative manufacturing:a review. Int J Adv Manuf Technol 41(1/2):132-144
32. Wei W, Liang PF (2018) A product platform architecture for cloud manufacturing. In:Proceedings of 2018 48th international conference on computers and industrial engineering, Auckland, New Zealand Afghah

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