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

doi:10.1007/s40436-020-00314-1

Advances in Manufacturing ›› 2020, Vol. 8 ›› Issue (3): 344-360.doi: 10.1007/s40436-020-00314-1

• • 上一篇

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

Mirsadegh Seyedzavvar¹, Hossein Abbasi², Mehdi Kiyasatfar³, Reza Najati Ilkhchi²

1 Faculty of Engineering, Adana Alparslan Türkeş University of Science and Technology, Adana, Turkey;
2 Faculty of Mechanical Engineering, University of Tabriz, Tabriz, Iran;
3 School of Science and Engineering, Khazar University, Baku, Azerbaijan

收稿日期:2019-11-28 修回日期:2020-02-23 发布日期:2020-09-10
通讯作者: Mirsadegh Seyedzavvar E-mail:mseyedzavvar@atu.edu.tr
基金资助:
The authors are grateful for the financial support from the Organization for Development of Young Talents of Khazar University, Sumqayit Techno Park (STP), and R&D of Tabriz Tractor Manufacturing Company. The technical support of the Central laboratory of Tabriz University, Nano Technology Laboratory of Khazar University, and Material Science Laboratory of ATÜ are also highly appreciated.

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

Mirsadegh Seyedzavvar¹, Hossein Abbasi², Mehdi Kiyasatfar³, Reza Najati Ilkhchi²

1 Faculty of Engineering, Adana Alparslan Türkeş University of Science and Technology, Adana, Turkey;
2 Faculty of Mechanical Engineering, University of Tabriz, Tabriz, Iran;
3 School of Science and Engineering, Khazar University, Baku, Azerbaijan

Received:2019-11-28 Revised:2020-02-23 Published:2020-09-10
Contact: Mirsadegh Seyedzavvar E-mail:mseyedzavvar@atu.edu.tr
Supported by:
The authors are grateful for the financial support from the Organization for Development of Young Talents of Khazar University, Sumqayit Techno Park (STP), and R&D of Tabriz Tractor Manufacturing Company. The technical support of the Central laboratory of Tabriz University, Nano Technology Laboratory of Khazar University, and Material Science Laboratory of ATÜ are also highly appreciated.

摘要/Abstract

摘要： 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

关键词: CuO nanofluids, Tribology, Lubrication, Wear, Coefficient of friction, Surface roughness

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.

参考文献

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

[1]	Wei Han, Feng-Zhou Fang. Investigation of electropolishing characteristics of tungsten in ecofriendly sodium hydroxide aqueous solution[J]. Advances in Manufacturing, 2020, 8(3): 265-278.
[2]	Ji-Peng Chen, Lin Gu, Guo-Jian He. A review on conventional and nonconventional machining of SiC particle-reinforced aluminium matrix composites[J]. Advances in Manufacturing, 2020, 8(3): 279-315.
[3]	Ben-Kai Li, Qing Miao, Min Li, Xi Zhang, Wen-Feng Ding. An investigation on machined surface quality and tool wear during creep feed grinding of powder metallurgy nickel-based superalloy FGH96 with alumina abrasive wheels[J]. Advances in Manufacturing, 2020, 8(2): 160-176.
[4]	Wei Zhao, Asif Iqbal, Ding Fang, Ning He, Qi Yang. Experimental study on the meso-scale milling of tungsten carbide WC-17.5Co with PCD end mills[J]. Advances in Manufacturing, 2020, 8(2): 230-241.
[5]	Xiao-Fen Liu, Wen-Hu Wang, Rui-Song Jiang, Yi-Feng Xiong, Kun-Yang Lin. Tool wear mechanisms in axial ultrasonic vibration assisted milling in-situ TiB₂/7050Al metal matrix composites[J]. Advances in Manufacturing, 2020, 8(2): 252-264.
[6]	Xiang-Ru Chen, Qi-Jie Zhai, Han Dong, Bao-Hua Dai, Hardy Mohrbacher. Molybdenum alloying in cast iron and steel[J]. Advances in Manufacturing, 2020, 8(1): 3-14.
[7]	Gang Shen, Ju-Fan Zhang, Feng-Zhou Fang. In vitro evaluation of artificial joints: a comprehensive review[J]. Advances in Manufacturing, 2019, 7(1): 1-14.
[8]	Mohammad Lotfi, Saeid Amini, Ihsan Yaseen Al-Awady. 3D numerical analysis of drilling process: heat, wear, and built-up edge[J]. Advances in Manufacturing, 2018, 6(2): 204-214.
[9]	Somvir Singh Nain, Dixit Garg, Sanjeev Kumar. Evaluation and analysis of cutting speed, wire wear ratio, and dimensional deviation of wire electric discharge machining of super alloy Udimet-L605 using support vector machine and grey relational analysis[J]. Advances in Manufacturing, 2018, 6(2): 225-246.
[10]	Ramanuj Kumar, Ashok Kumar Sahoo, Purna Chandra Mishra, Rabin Kumar Das. Comparative investigation towards machinability improvement in hard turning using coated and uncoated carbide inserts: part I experimental investigation[J]. Advances in Manufacturing, 2018, 6(1): 52-70.
[11]	Ravindra Nath Yadav. Development and experimental investigation of duplex turning process[J]. Advances in Manufacturing, 2017, 5(2): 149-157.
[12]	A. Pramanik, A. R. Dixit, S. Chattopadhyaya, M. S. Uddin, Yu Dong, A. K. Basak, G. Littlefair. Fatigue life of machined components[J]. Advances in Manufacturing, 2017, 5(1): 59-76.
[13]	M. S. Uddin, Binh Pham, Ahmed Sarhan, Animesh Basak, Alokesh Pramanik. Comparative study between wear of uncoated and TiAlN-coated carbide tools in milling of Ti6Al4V[J]. Advances in Manufacturing, 2017, 5(1): 83-91.
[14]	Vedat Savas, Cetin Ozay, Hasan Ballikaya. Experimental investigation of cutting parameters in machining of 100Cr6 with tangential turn-milling method[J]. Advances in Manufacturing, 2016, 4(1): 97-104.
[15]	D. Biermann, H. Abrahams, M. Metzger. Experimental investigation of tool wear and chip formation in cryogenic machining of titanium alloys[J]. Advances in Manufacturing, 2015, 3(4): 292-299.

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

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

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价