Multi response optimization of friction stir welding in air and water by analytic hierarchy process and VIKOR method

Document Type : Research Note

Authors

1 Department of Mechanical Engineering, Dr. M.G.R Educational and Research Institute, Maduravoyal, Chennai-600095, India

2 Faculty of Mechanical Engineering, Dr. M.G.R Educational and Research Institute, Maduravoyal, Chennai-600095, India

Abstract

Friction stir welding of Titanium sheets is carried out under air and water environment and the tensile properties of the joints made are measured. The tool rotational speed and tool traversing speed which significantly influence the tensile properties of the welded joints are considered as input process parameters. This work deals with the application of Analytic hierarchy process to calculate the weights of the relative importance of the output responses using the pairwise comparison of responses and checked for the consistency and acceptability of the assumed comparison. Also, the VIKOR optimization technique, a multi-response multi criterion method, is used for determining the optimum process parameters. From the VIKOR optimization method, it is observed that the higher tool rotational speed and lower tool traversing speed are the optimum process parameters in both conventional and under water FSW. The results from the experimental measurements and the study of microstructure supports the results obtained from VIKOR optimization method.

Keywords

Main Subjects

References

References:
1. Memon, S., Tomkow, J., and Derazkola, H.A. "Thermo-mechanical simulation of underwater friction stir welding of low carbon steel", Material, 14(17), p. 4953 (2021). DOI: https://doi.org/10.3390/ma14174953.
2. SaravanaKumar, R. and Rajasekaran, T. "Optimizing the underwater friction stir welding parameters to enhance the joint strength of armour grade aluminium alloy AA5083 butt joints", Materials Today: Proceedings, 47, pp. 6999-7005 (2021). DOI: https://doi.org/10.1016/j.matpr.2021.05.280.
3. Ghiasvand, A., Yavari, M.M., Tomkow, J., et al."Investigation of mechanical and microstructural properties of welded specimens of AA6061-T6 alloy with friction stir welding and parallel-friction stir welding methods", Material, 14, p. 6003 (2021). DOI: https://doi.org/10.3390/ma14206003.
4. Lombard, H., Hattingh, D.G., Steuwer, A., et al. "Optimising FSW process parameters to minimise defects and maximise fatigue life in 5083-H321 aluminium alloy", Engineering Fracture Mechanics, 75, pp. 341- 354 (2008). DOI: https://doi.org/10.1016/j.engfracmech.2007.01.026.
5. Zhang, J., Liu, K., Huang, G., et al. "Optimizing the mechanical properties of friction stir welded dissimilar joint of AM60 and AZ31 alloys by controlling deformation behavior", Materials Science and Engineering, A, 773, p. 138839 (2020). DOI: https://doi.org/10.1016/j.msea.2019.138839.
6. Sevvel, P. and Jaiganesh, V. "Characterization of mechanical properties and microstructural analysis of friction stir welded AZ31B Mg alloy through optimized process parameters", Procedia Engineering, 97, pp. 741-751 (2014). DOI: https://doi.org/10.1016/j.proeng.2014.12.304.
7. Xu, X., Zhang, C., Derazkola, H.A., et al. "UFSW tool pin profile effects on properties of aluminium-steel joint", Vacuum, 192, p. 110460 (2021).DOI: https://doi.org/10.1016/j.vacuum.2021.110460.
8. Derazkola, H.A. and Khodabakhshi, F. "Underwater submerged dissimilar friction-stir welding of AA5083 aluminum alloy and A441 AISI steel", The International Journal of Advanced Manufacturing Technology, 102(9-12), pp. 4383-4395 (2019). DOI: https://doi.org/10.1007/s00170-019-03544-1.
9. Talebizadehsardari, P., Musharavati, F., Khan, A., et al. "Underwater friction stir welding of Al-Mg alloy: Thermo mechanical modeling and validation", Materials Today Communications, 26, p. 101965 (2021). DOI: https://doi.org/10.1016/j.mtcomm.2020.101965.
10. Mozammil, S., Karloopia, J., Verma, R., et al. "Mechanical response of friction stir butt weld Al-4.5modelling and optimization", Journal of Alloys and Compounds, 826, p. 154184 (2020). DOI: https://doi.org/10.1016/j.jallcom.2020.154184.
11. Zhang, H. and Liu, H. "Mathematical model and optimization for underwater friction stir welding of a heat-treatable aluminum alloy", Materials and Design, 45, pp. 206-211 (2013). DOI: http://dx.doi.org/10.1016/j.matdes.2012.09.0 22.
12. Ghaffarpour, M., Aziz, A., and Hejazi, T.-H. "Optimization of friction stir welding parameters using multiple response surface methodology", Journal of Materials: Design and Applications, 7, pp. 571-583 (2015). DOI: https://doi.org/10.1177/1464420715602139.
13. Guleryuz, G. "Relationship between FSW parameters and hardness of the ferritic steel joints: Modeling and optimization", Vacuum, 178, p. 109449 (2020). DOI: https://doi.org/10.1016/j.vacuum.2020.109449.
14. Shashi Kumar, S., Murugan, N., and Ramachandran, K.K. "Identifying the optimal FSW process parameters for maximizing the tensile strength of friction stir welded AISI 316L butt joints",Measurement, 137, pp. 257-271 (2020). DOI: https://doi.org/10.1016/j.measurement.2019.01.023.
15. Yuvaraj, K.P., Ashoka Varthanan, P., Haribabu, L., et al. "Optimization of FSW tool parameters for joining dissimilar AA7075-T651and AA6061 aluminium alloys using Taguchi technique", Materials Today: Proceeding, 45, pp. 919-925 (2021). DOI: https://doi.org/10.1016/j.matpr.2020.02.942.
16. Lakshminarayanan, A.K. "Enhancing the properties of friction stir welded stainless steel joints via multicriteria optimization", Archives of Civil and Mechanical Engineering, 16, pp. 605-617 (2016). DOI: http://dx.doi.org/10.1016/j.acme.2016.03.012.
17. Heidarzadeh, A., Barenji, R.V., Khalili, V., et al. "Optimizing the friction stir welding of the ff=fi brass plates to obtain the highest strength and elongation", Vacuum, 159, pp. 152-160 (2019). DOI:https://doi.org/10.1016/j.vacuum.2018.10.036.
18. Silva, A.C.F., Braga, D.F.O., Figueiredo, M.A.V.D., et al. "Friction stir welded T-joints optimization", Materials and Design, 55, pp. 120-127 (2014). DOI: http://dx.doi.org/10.1016/j.matdes.2013.09.016.
19. Boukraa, M., Lebaal, N., Mataoui, A., et al. "Friction stir welding process improvement through coupling an optimization procedure and three-dimensional transient heat transfer numerical analysis", Journal of Manufacturing Processes, 34, pp. 566-578 (2018). DOI: https://doi.org/10.1016/j.jmapro.2018.07.002.
20. Medhi, T., Hussain, S.A.I., Roy, B.S., et al. "An intelligent multi-objective framework for optimizing friction-stir welding process parameters", Applied Soft Computing Journal, 104, p. 107190 (2021). DOI: https://doi.org/10.1016/j.asoc.2021.107190.
21. Mohammadzadeh Jamalian, H., Tamjidi Eskandar, M., Chamanara, A., et al. "An artificial neural network  model for multi-pass tool pin varying FSW of AA5086- H34 plates reinforced with Al2O3 nanoparticles and optimization for tool design insight", CIRP Journal of Manufacturing Science and Technology, 35, pp. 69-79 (2021).DOI: https://doi.org/10.1016/j.cirpj.2021.05.007.
22. Heidarzadeh, A., Testik, O.M., Guleryuz, G., et al. "Development of a fuzzy logic based model to elucidate the effect of FSW parameters on the ultimate tensile strength and elongation of pure copper joints", Journal of Manufacturing Processes, 53, pp. 250-259 (2020). DOI: https://doi.org/10.1016/j.jmapro.2020.02.020.
23. Wakchaure, K.N., Thakur, A.G., Gadakh, V., et al. "Multi-objective optimization of friction stir welding of aluminium alloy 6082-T6 using hybrid Taguchigrey relation analysis-ANN method", Materials Today: Proceedings, 5(2), pp. 7150-7159 (2018). DOI: https://doi.org/10.1016/j.matpr.2017.11.380.
24. Shehabeldeen, T.A., Elaziz, M.A., Elsheikh, A.H., et al. "Modeling of friction stir welding process using adaptive neuro-fuzzy inference system integrated with harris hawks optimize", Journal of Materials Research and Technology, 8(6), pp. 5882-5892 (2019). DOI: https://doi.org/10.1016/j.jmrt.2019.09.060.
25. Banik, A., Saha, A., Deb Barma, J., et al. "Determination of best tool geometry for friction stir welding of AA 6061-T6 using hybrid PCA-TOPSIS optimization method", Measurement, 173, p. 108573 (2021). DOI: https://doi.org/10.1016/j.measurement.2020.108573.
26. Caseiro, J.F., Valente, R.A.F., Andrade-Campos, A., et al. "On the elasto-plastic buckling of Integrally Stiffened Panels (ISP) joined by Friction Stir Welding (FSW): Numerical simulation and optimization algorithms", International Journal of Mechanical Sciences, 76, pp. 49-59 (2013). DOI: http://dx.doi.org/10.1016/j.ijmecsci.2013.09.002.
27. Pitchipoo, P., Muthiah, A., Jeyakumar, K., et al. "Friction stir welding parameter optimization using novel multi objective dragon y algorithm", International Journal of Lightweight Materials and Manufacture, 4, pp. 460-467 (2021). DOI: https://doi.org/10.1016/j.ijlmm.2021.06.006.
28. Rahman, M.F., Amin, M.B., and Parvez, M. "Application of AHP in development of multi-criteria ergonomic approach for choosing the optimal alternative for material handling- a case study and software development to facilitate AHP calculation", International Journal of Engineering Research & Technology, 3(6), pp. 1064- 1074 (2014).
29. Blagojevic, B., Athanassiadis, D., Spinelli, R., et al. "Determinig the relative importance of factors affecting the success of innovations in forest technology using AHP", Journal of Multi-Criteria Decision Analysis, 27(1-2), pp. 129-140 (2020). DOI:https://doi.org/10.1002/mcda.1670.
30. Tong, L.I., Chen, C.C., and Wang, C.H. "Optimization of multi-response processes using the VIKOR method", International Journal of Advanced Manufacturing Technology, 31, pp. 1049-1057 (2007). DOI: https://doi.org/10.1007/s00170-005-0284-6.
31. Aravind, A.P., Suryaprakash, S., Vishal, S., et al. "Optimization of welding parameters in CMT welding of Al5083 alloys using VIKOR optimization method", IOP Conf. Series: Materials Science and Engineering, 912, p. 032035 (2020). DOI: http://doi.org/10.1088/1757-899X/912/3/032035.
32. Aravind, A.P., Kurmi, J.S., Swamy, P.M., et al. "Optimization of welding parameters in laser welding of Ti6Al4V using VIKOR optimization method", Materials Today: Proceedings, 45(2), pp. 592-596 (2021). DOI: https://doi.org/10.1016/j.matpr.2020.02.388.
33. Peng, Y., Li, T., Bao, C., et al. "Performance analysis and multi-objective optimization of bionic dendritic furcal energy-absorbing structures for trains", International Journal of Mechanical Sciences, 246, p. 108145 (2023). DOI: https://doi.org/10.1016/j.ijmecsci.2023.108145.
34. Singh, S.K., Prabhakar, S., Rao, D.K., et al. "Multiresponse optimization of EDMed parameters of Ti-6Al-4 V alloy using entropy integrated -VIKOR method", Materials Today: Proceedings, 62, pp. 1163-1168 (2022). DOI: https://doi. org/10.1016/j.matpr.2022.04.348.
35. Swaraj Kumar, B., Varghese, J., and Jacob, J. "Optimal thermochemical material selection for a hybrid thermal energy storage system for low temperature applications using multi criteria optimization technique", Materials Science for Energy Technologies, 5, pp. 452-472 (2022). DOI: https://doi.org/10.1016/j.mset.2022.10.005.
36. Yang, Y., Wang, H., Zhao, Y., et al. "Three-way decision approach for water ecological security evaluation and regulation coupled with VIKOR: A case study in Beijing-Tianjin-Hebei region", Journal of Cleaner Production, 379(1), p. 134666 (2022). DOI: https://doi.org/10.1016/j.jclepro.2022.134666.
37. Meniz, B. and Ozkan, E.M. "Vaccine selection for COVID-19 by AHP and novel VIKOR hybrid approach with interval type-2 fuzzy sets", Engineering Applications of Artificial Intelligence, 119, p. 105812 (2023). DOI: https://doi.org/10.1016/j.engappai.2022.105812.
Scientia Iranica
Volume 31, Issue 4 - Serial Number 4
Transactions on Mechanical Engineering (B)
March and April 2024
Pages 346-357

Files

Share

How to cite

Statistics