Multivariate modelling of effectiveness of lubrication of Ti-6Al-4V titanium alloy sheet using vegetable oil-based lubricants

• Autorzy: Trzepieciński Tomasz , Szpunar Marcin

Identyfikatory

DOI

10.2478/adms-2021-0009

• Języki publikacji: EN

Abstrakty

EN

The article presents the results of modelling the friction phenomenon using artificial neural networks and analysis of variance. The test material was composed of strip specimens made of 0.5-mm-thick alpha-beta Grade 5 (Ti-6Al-4V) titanium alloy sheet. A special tribotester was used in the tests to simulate the friction conditions between the punch and the sheet metal in the sheet metal forming process. A test called the strip drawing test has been conducted in conditions in which the sheet surface is lubricated with six environmentally friendly oils (palm, coconut, olive, sunflower, soybean and linseed). Based on the results of the strip drawing test, a regression model and an artificial neural network model were built to determine the complex interactions between the process parameters and the friction coefficient. A multilayer perceptron with one hidden layer and eight neurons in this layer showed the best fit to the training data. The network training was conducted using three algorithms, i.e. Levenberg-Marquardt, back propagation and quasi-Newton. Taking into consideration both the coefficient of determination R² (0.962) and S.D. ratio (0.272), the best regression characteristics were presented by the network trained using the Levenberg-Marquardt algorithm. From the response surfaces of the quadratic regression model it was found that an increase in the density of lubricant at a specific pressure causes a reduction in the coefficient of friction. Low density and high kinematic viscosity of the oil leads to a high coefficient of friction.

Słowa kluczowe

EN

coefficient of friction; sheet metal; sheet metal forming; Ti-6Al-4V; titanium alloy

PL

współczynnik tarcia; blacha; formowanie blachy; Ti-6Al-4V; stop tytanu

• Wydawca: Politechnika Gdańska
• Czasopismo: Advances in Materials Science
• Rocznik: 2021
• Tom: Vol. 21, nr 2(68)
• Strony: 26--39
• Opis fizyczny: Bibliogr. 27 poz., tab., il., wykr.

Twórcy

autor

Trzepieciński Tomasz

• Rzeszow University of Technology, Department of Materials Forming and Processing, Rzeszów, Poland

autor

Szpunar Marcin

• Rzeszow University of Technology, Doctoral School of Engineering and Technical Sciences, Rzeszów, Poland

Bibliografia

• 1. Trzepiecinski T., Lemu H.G.: Recent developments and trends in the friction testing for conventional sheet metal forming and incremental sheet forming. Metals 10 (2020) 47.
• 2. Trzepieciński T., Fejkiel R.: On the influence of deformation of deep drawing quality steel sheet on surface topography and friction. Tribology International 115 (2017) 78–88.
• 3. Zafaruddin F., Dolas D.R.: Experimental investigation of organic brake pad. International Journal of Advance Research and Innovative Ideas in Education 2(6) (2016) 213–219.
• 4. https://mail.pk.edu.pl/~kmiernik/dydaktyka/materialy/obrplast/lab3.pdf (dostęp: 25.03.2021).
• 5. Dou S., Xia J. Analysis of sheet metal forming (stamping process): A study of the variable friction coefficient on 5052 aluminum alloy. Metals 9 (2019) 853.
• 6. Dyja K., Adamus J.: Badania nad doborem smarów technologicznych do tłoczenia blach aluminiowych i tytanowych. Tribologia 3 (2014) 19-28.
• 7. Jaworski J., Trzepiecinski T.: Research on durability of turning tools made of low-alloy high-speed steels. Kovove Materialy-Metallic Materials 54(1) (2016) 17–25.
• 8. Jaworski J., Kluz R., Trzepiecinski T.: Operational tests of wear dynamics of drills made of low-alloy high-speed HS2-5-1 steel. Eksploatacja i Niezawodnosc-Maintenance and Reliability 18(2) (2016) 271–277.
• 9. Ma J., Yang H., Li H., i in.: Tribological behaviors between commercial pure titanium sheet and tools in warm forming. Transactions of Nonferrous Metals Society of China 25 (2015) 2924–2931.
• 10. Martínez C., Briones F., Araya N. i in.: Influence of the synthesis technique on tribological behavior of a Ti-6Al-4V alloy. Materials Letters 281 (2020), 128627.
• 11. Makhkamov A.: Tribology in sheet metal forming. PhD Thesis, Universidade do Porto, Porto 2017.
• 12. Lovell M.R., Kabir M.A., Menezes P.L. i in.: Influence of boric acid additive size on green lubricant performance. Philosophical Transactions of the Royal Society A. 368 (2010) 4851–4868.
• 13. Trzepieciński T.: Tribological performance of environmentally friendly bio-degradable lubricants based on a combination of boric acid and bio-based oils. Materials 13 (2020) 3892.
• 14. Fydrych D., Świerczyńska A., Rogalski G. i in.: Application of multivariate analysis methods in welding engineering. Biuletyn Instytutu Spawalnictwa 5 (2018) 137–145.
• 15. Ikpambese K.K., Lawrence E.A. Comparative analysis of multiple linear regression and artificial neural network for predicting friction and wear of automotive brake pads produced from palm kernel shell. Tribology in Industry 40(4) (2018) 565–573.
• 16. Sudheer M., Prabhu R., Raju K. i in.: Modeling and analysis for wear performance in dry sliding of epoxy/glass/PTW composites using full factorial techniques. International Scholarly Research Notices 2013 (2013) 624813.
• 17. Monikandan V.V., Jacob J.C., Joseph M.A. i in.: Statistical analysis of tribological properties of aluminum matrix composites using full factorial design. Transactions of the Indian Institute of Metals 68 (2015) 53–57.
• 18. Egala R., Jagadeesh G.V., Setti S.G.: Experimental investigation and prediction of tribological behavior of unidirectional short castor oil fiber reinforced epoxy composites. Friction 9 (2021) 250–272.
• 19. Yunus M., Alsoufi M.S.: Multi-output optimization of tribological characteristics control factors of thermally sprayed industrial ceramic coatings using hybrid Taguchi-grey relation analysis. Friction 4(3) (2016) 208–216.
• 20. ASTM B348. Standard specification for titanium and titanium alloy bars and billets.
• 21. ASTM F1108 – 14. Standard specification for titanium-6Aluminum-4Vanadium alloy castings for surgical implants.
• 22. Bahari A., Lewis R., Slatter T.: Friction and wear phenomena of vegetable oil-based lubricants with additives at severe sliding wear conditions. Tribology Transactions 61 (2018) 207–219.
• 23. Karmakar G., Ghosh P., Sharma B.K. Chemically modyfying vegetable oils to prepare green lubricants. Lubricants 5 (2017) 44.
• 24. Mobarak H.M., Mohamad E.N., Masjuki H.H. i in.: The prospects of biolubricants as alternatives in automotive applications. Renewable and Sustainable Energy Reviews 33 (2014) 34–43.
• 25. Trzepiecinski, T. Effect of the plastic strain and drawing quality on the frictional resistance of steel sheets. Acta Metallurgica Slovaca 26(2) (2020) 42–44.
• 26. Sulaiman M.H., Christiansen P., Bay N.: Influence of tool texture on friction and lubrication in strip reduction. Procedia Engineering 207 (2017) 2263–2268.
• 27. Puc M. Artificial neural network model of the relationship between Betula pollen and meteorological factors in Szczecin (Poland). International Journal Biometeorology 56 (2012) 395–401.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).