Investigation of gas metal arc welding process parameters of aluminium alloy weldment using Taguchi-grey-fuzzy integrated approach

Document Type : Article

Authors

1 Department of Mechanical Engineering, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India

2 Department of Mechanical Engineering, Sri Ramakrishna Engineering College, Tamil Nadu, India

3 Department of Mechanical Engineering, Amrita College of Engineering and Technology, Nagercoil, Tamil Nadu, India

Abstract

Globally, aluminium alloys are being used in many industries. Application of aluminium alloys is realized by many manufacturing processes in which joining processes are inevitable. Joining of aluminium alloys is achieved by various welding processes. One of the appropriate welding processes used to join aluminium alloy is Gas Metal Arc Welding (GMAW). This paper investigates the effect of process parameters of the GMAW process while welding AA 6351 aluminium alloy weldment with the help of an integrated Taguchi–Grey–Fuzzy approach. Taguchi L-16 array was designed by using an orthogonal method to conduct the experiments. From the experimental results, Signal-to-Noise Ratios (S/N ratio) were calculated from which Grey Relational Grades (GRG) were computed. These computed Grey Relational Grades were used as input for the fuzzy controller to find the Grey Fuzzy Relational Grades (GFRG), by which optimized process parameters were found and validated. Furthermore, Analysis of Variance (ANOVA) was used to identify the contributions of the GMAW process parameters over the responses. Subsequently, the effects of process parameters on the weldments were also discussed in detail. By identifying the optimized process parameters and contributing process parameters, the quality of weld joints is improved.

Keywords

References

References:
1. Benyounis, K.Y. and Olabi A.G. "Optimization of different welding processes using statistical and numerical approaches-A reference guide", Advances in Engineering Software, 39(6), pp. 483-496 (2008).
2. Parida, B. and Pal, S. "Fuzzy assisted grey Taguchi approach for optimization of multiple weld quality properties in friction stir welding process", Science and Technology of Welding and Joining, 20(1), pp. 35-41 (2015).
3. Sahu, P.K., Kumari, K., Pal, S., et al. "Hybrid fuzzygrey-Taguchi based multi weld quality optimization of Al/Cu dissimilar friction stir welded joints", Advances in Manufacturing, 4(3), pp. 237-247 (2016).
4. Chandel, R.S., Seow, H.P., and Cheong, F.L. "Effect of increasing deposition rate on the bead geometry of submerged arc welds", Journal of Materials Processing Technology, 72(1), pp. 124-128 (1997).
5. Kim, I.S., Jeong, Y.J., Son, I.J., et al. "Sensitivity analysis for process parameters influencing weld quality in robotic GMA welding process", J. Mater. Process Technol., 140, pp. 676-681 (2003-a).
6. Kim, I.S., Son, K.J., Yang, Y.S., et al. "Sensitivity analysis for process parameters in GMA welding processes using a factorial design method", Int. J. Mach. Tools Manuf., 43, pp. 763-769 (2003-b).
7. Satheesh, M. and Dhas, J.E.R. "Multi objective optimization of flux cored arc weld parameters using hybrid grey-fuzzy technique", The Journal of Engineering Research, 11(1), pp. 23-33 (2013).
8. Kumar, A. and Maheshwari, S. "Advanced materials optimization of submerged arc welding rutile based  flux constituents by hybrid grey, fuzzy and Taguchi analysis", Advanced Materials Manufacturing & Characterization, 5(2), pp. 63-70 (2015).
9. Sarkar, A., Majumder, A., Pawar, M., et al. "Optimization of process parameters of submerged arc welding by using grey-fuzzy-based Taguchi method for AISI 1518 grade steel", Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 228(11), pp. 1-10 (2014).
10. Saravanan, S. and Pitchipoo, P. "Optimization of GMAW parameters to improve the mechanical properties", Applied Mechanics and Materials, Trans Tech Publications, Switzerland, 813-814, pp. 456-461 (2015).
11. Hould, C.P.T., Submerged Arc Welding, Second Edn., Abington Publishing, Cambridge, England (1989).
12. Jeffus, F.L., Welding: Principles and Applications, Thomson/Delmar, 5th Edn. (2004).
13.  Ozgormus, E., Senocak, A.A., and Goren, H.G. "An integrated fuzzy QFD-MCDM framework for personnel selection problem", Scientia Iranica, 28(5), E, pp. 2972-2986 (2021).
14. Datta, S., Asish, B., and Pradip Kumar, P. "Application of Taguchi philosophy for parametric optimization of bead geometry and HAZ width in submerged arc welding using a mixture of fresh  flux and fused flux", Int. J. Adv. Manuf. Technol., 36(7-8), pp. 689-698 (2008).
15. Kannan, T. and Yoganandh, J. "Effect of process parameters on clad bead geometry and its shape relationships of stainless steel claddings deposited by GMAW", Int. J. Adv. Manuf. Technol., 47, pp. 1083- 1095 (2010).
16. Senthilkumar, B. and Kannan, K. "Effect of  flux cored arc welding process parameters on bead geometry in super duplex stainless steel claddings", Meas. J. Int. Meas. Confed., 62, pp. 127-136 (2015).
17. Ebrahimi Qazvini, Z., Haji, A., and Mina, H. "A fuzzy solution approach to supplier selection and order allocation in green supply chain considering the locationrouting problem", Scientia Iranica, 28(1), pp. 446-464 (2021).
18. Moghaddam, M.A., Golmezergi, R., and Kolahan, F. "Multi-variable measurements and optimization of GMAW parameters for API-X42 steel alloy using a hybrid BPNN-PSO approach", Measurement, 92, pp. 279-287 (2016).
19. Rostami, S., Toghraie, D., and Shabani, B. "Measurement of the thermal conductivity of MWCNTCuO/ water hybrid nano fluid using Artificial Neural Networks (ANNs)", J. Therm. Anal. Calorim., 143, pp. 1097-1105 (2021-a).
20. He, W., Ruhani, B., Toghraie, D., et al. "Using of Artificial Neural Networks (ANNs) to predict the thermal conductivity of zinc oxide-silver (50%-50%)/water hybrid Newtonian nanofluid", International Communications in Heat and Mass Transfer, 116(104645), pp. 1-8 (2020).
21. Kurtulmus, M. "Effects of welding parameters on penetration depth in mild steel A-TIG welding", Scientia Iranica, 26(3), pp. 1400-1404 (2019).
22. Kam, M., Ipekci, A., and Sengul, O. "Taguchi optimization of fused deposition modeling process parameters on mechanical characteristics of PLA + filament material", Scientia Iranica, 29(1), pp. 79-89 (2022).
23. Azadi Moghaddam, M. and Kolahan, F. "Modeling and optimization of the electrical discharge machining process based on a combined artificial neural network and particle swarm optimization algorithm", Scientia Iranica, 27(3), pp. 1206-1217 (2020).
24. Rostami, S., Toghraie, D., and Esfahani, M.A. "Predict the thermal conductivity of SiO2/water-ethylene glycol (50:50) hybrid nanofluid using artificial neural network", J. Therm. Anal. Calorim., 143, pp. 1119- 1128 (2021-b).
25. Garg, H. and Kaur, G. "Extended TOPSIS method for multi-criteria group decision-making problems under cubic intuitionistic fuzzy environment", Scientia Iranica, 27(1), pp. 396-410 (2020).
26. Delir Nazarlou, R., Nemati Akhgar, B., and Omidbakhsh, F. "Optimization of friction stir welding parameters with Taguchi method for maximum electrical conductivity in Al-1080 welded sections", Scientia Iranica, 28(4), pp. 2250-2258 (2021).
27. Toghraie, D., Sina, N., Adavoodi Jolfaei, N., et al. "Designing an Artificial Neural Network (ANN) to predict the viscosity of silver/ethylene glycol nanofluid at different temperatures and volume fraction of nanoparticles", Physica A: Statistical Mechanics and its Applications, 534(122142), pp. 1-10 (2019).
28. Tavakkoli Nabavi, M., Azadi Moghaddam, M., Fardfarimani, N., et al. "Comparative modeling of abrasive waterjet machining process based on OA-Taguchi and D-optimal approach and optimization using simulated annealing algorithm", Scientia Iranica, 29(3), pp. 1276-1287 (2021).
29. Bahrami, H. and Kolahan, F. "Mathematical modeling and optimization of weld bead geometry in cladding by  flux cored arc welding", Proceedings of 11th Iranian Conference on Manufacturing Engineering, pp. 329-335 (2010).
30. Zadeh, L.A. "Fuzzy sets", Information and Control, 8(3), pp. 338-353 (1965).
31. Srihari, T. "Submerged arc welding of high strength low alloy steels", Ph.D. Thesis, IIT, Delhi (1992).
32. Sowrirajan, M., Koshy Mathews, P., Vijayan, S., et al. "Investigations on effect of FCAW process variables in heat loss reduction clad layers", International Journal of ChemTech Research, 10(2), pp. 948-960 (2017).
33. Hashmi, S., Gilmar Ferreira Batalha, Chester J. Van Tyne, Bekir Yilbas, Emin Bayraktar, Comprehensive Materials Processing, Welding and Bonding Technologies, 6, ISBN: 978-0-08-096533-8 (2014).
34. Samir Ali Amin Alrabii and Tarek, Mohammed Ali Ali "Modeling and optimization the influence of CO2- MAG welding parameters on the weld joint shape factors", Journal of Engineering, 21(10), pp. 70-89 (2015).
Scientia Iranica
Volume 29, Issue 6 - Serial Number 6
Transactions on Mechanical Engineering (B)
November and December 2022
Pages 3084-3097

Files

Share

How to cite

Statistics