Authors:
Rasha M. Hussien,Mohsin Abdullah Al-Shammari,DOI NO:
https://doi.org/10.26782/jmcms.2021.06.00007Keywords:
dissimilar aluminum plates,Particle Swarm Optimization,Taguchi,Abstract
Friction stir welding (FSW) has many advantages when compared with another fusion welding. The experimental analysis and optimization of friction stir welding (FSW) were done to obtain desired mechanical properties of dissimilar aluminum welded plates (2024T3 and 7075T6). The friction stir welding process was done on aluminum plates (2024T3 and 7075T6) for different three rotating speeds (710, 1120 and 1800), three welding speeds (25, 50 and 77), three different steel tools (Square, cylindrical and Hexagonal) and 2° title angle. The different tests of welding were done according to the orthogonal matrix of experimental design analysis, then a tensile test was done to calculate the ultimate stress to get the welding efficiency. The optimum welding environment led to the maximum efficiency was obtained by these methods (Taguchi, Particle Swarm Optimization and new modified Particle Swarm Optimization). Particle swarm optimization (and its new modification) used an artificial neural network to find the relation between the input and output parameters. The results showed that when the rotating speed is increased and welding speed is decreased (but this conclusion depends on tool shape) the welding efficiency is increased. The present study showed that the modified PSO is the best method to find the optimum welding environment as compared with experimental results.Refference:
I. ASM Handbook, “Properties and Selection: Non-Ferrous Alloys and Special Purposes Materials”, American Society for Metals, Vol. 2, (1992).
II. D.M. Nikam, N.V. Paithankar, A.S. More, A. B. Bansode, P.P. Darade, “Experimental Analysis to Optimize the Process Parameter of Friction Stir Welding of Aluminum Alloy”, International Research Journal of Engineering and Technology, e-ISSN: 2395 -0056, Volume: 04 Issue: 05 | May -2017.
III. Jacek M. Zurada,” Introduction to artificial neural systems”, ISBN 0-3 14-93391 -3, 8 Copyright@1992
IV. J. Kennedy, R. Eberhart, Particle swarm optimization, in IEEE International Conference on Neural Networks, Vol. 4, 1995, pp. 1942-1948.
V. J.R. Davis, p351-416, ” Alloying: Understanding the Basics”, Copyright 2001 ASM International, DOI:10.1361/autb2001p351
VI. K. Mallieswaran, R. Padmanabhan & V. Balasubramanian, “Friction stir welding parameters optimization for tailored welded blank sheets of AA1100 with AA6061 dissimilar alloy using response surface methodology”, Advances in Materials and Processing Technologies ISSN: 2374-068X (Print) 2374-0698.
VII. Lam Suvarna Raju, Venu Borigorla, : ‘MULTI OBJECTIVE OPTIMIZATION OF FSW PROCESS PARAMETERS USING GENETIC ALGORITHM AND TLBO ALGORITHM’. J. Mech. Cont.& Math. Sci., Vol.-15, No.-7, July (2020) pp 480-494. DOI : 10.26782/jmcms.2020.07.00042
VIII. Masayuki Aonuma and Kazuhiro Nakata, “Dissimilar Metal Joining of 2024 and 7075 Aluminum Alloys to Titanium Alloys by Friction Stir Welding”, Materials Transactions, Vol. 52, No. 5 (2011) pp. 948 to 952.
IX. Murali Ambekar, Jayant Kittur, ” Multiresponse optimization of friction stir welding process parameters by an integrated WPCA-ANN-PSO approach”, Materials Today: Proceedings, First International Conference on Recent Advances in Materials and Manufacturing 2019.
X. Mohammad Hasan Shojaeefard, Reza Abdi Behnagh, Mostafa Akbari ,Mohammad Kazem Besharati Givi, Foad Farhani, ” Modelling and Pareto optimization of mechanical properties of friction stir welded AA7075/AA5083 butt joints using neural network and particle swarm algorithm”, Materials and Design 44 (2013) 190–198.
XI. Nilesh Kumar, Wei Yuan, Rajiv S. Mishra, “Friction Stir Welding of Dissimilar Alloys and Materials”, ISBN: 978-0-12-802418-8 Copyright@2015 Elsevier.
XII. Nizar Faisal Alkayem, Biswajit Parida, Sukhomay Pal, ” Optimization of friction stir welding process parameters using soft computing “, Springer-Verlag Berlin Heidelberg 2016, Soft Comput, DOI 10.1007/s00500-016-2251-6
XIII. R. Padmanaban, R. Vaira Vignesh, A. P. Povendhan, A. P. Balakumharen, ” Optimizing the tensile strength of friction stir welded dissimilar aluminium alloy joints using particle swarm optimization”, Materials Today: Proceedings 5 (2018) 24820–24826 ScienceDirect.
XIV. Radhika chada, N. Shyam Kumar, : ‘INVESTIGATION OF MICRO STRUCTURE AND MECHANICAL PROPERTIES OF FRICTION STIR WELDED AA6061 ALLOY WITH DIFFERENT PARTICULATE REINFORCEMENTS ADDITION’. J. Mech. Cont.& Math. Sci., Vol.-15, No.-4, April (2020) pp 264-278. DOI : 10.26782/jmcms.2020.04.00020.
XV. Rasha M Hussien and Mohsin Abdullah Al-Shammari, “Optimization of Friction Stir Welded Aluminium Plates by the New Modified Particle Swarm Optimization”, IOP Conference Series: Materials Science and Engineering2021 IOP Conf. Ser.: Mater. Sci. Eng. 1094 (2021) 012156, doi:10.1088/1757-899X/1094/1/012156.
XVI. Ranjit K. Roy, ” Design of Experiments Using the Taguchi Approach: 16 Steps to Product and Process Improvement”, ISBN 0-471-36101-1, copyright 2001 by john Wiley.
XVII. Singiresu S. Rao, “Engineering Optimization Theory and Practice”, JOHN WILEY & SONS, INC 2009, ISBN 978-0-470-18352-6
XVIII. Seong Y.K., Seung B.J., and Chang C.S.”Mechanical properties of copper to titanium joint by friction welding “Journal of material science PP.1281-1287. (2003).
XIX. Thella babu rao, “optimization of friction stir welding parameters during welding dissimilar aluminium alloys”, international journal of mechanical engineering and technology volume 9, issue 5, May 2018, pp. 333–340, article id: ijmet_09_05_037.
XX. ” X12 / X210Cr12 / 1.2080″, https://www.plienmetas.lt/irankinis-plienas-saltam-apdirbimui/x12-x210cr12-1-2080/