Parameter Optimization for Friction Stir Welding AA1100

Abstract:

Friction stir welding (FSW) has become a potential solid state joining technique with considerable advantages over conventional joining process. Defect-free friction stir welded joints with high joint strength are obtained when optimum process parameters are used. Although a large number of parameters govern the FSW process, the tool rotation speed, Welding speed and tool geometry are key parameters that influence the joint strength. In this work, a statistical model relating process parameters and the tensile strength (TS) of friction stir welded AA1100 joints is build using response surface methodology. The four independent variables are tool rotational speed (TRS), welding speed (WS), shoulder diameter (SD) and pin diameter (PD). Central Composite design is used and Analysis of Variance at 95% confidence level was applied to assess the adequacy of the developed model. Genetic algorithm is used for optimizing the parameters. The optimum process parameter values predicted using the genetic algorithm are as follows. Tool rotation speed: 1001.9 rpm; welding speed: 62 mm/min; shoulder diameter: 17.8 mm and pin diameter: 6.5 mm. The corresponding tensile strength of the joints is 73.1556 MPa

• Periodical: Applied Mechanics and Materials (Volumes 813-814)
• Pages: 462-466
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.813-814.462
• Online since: November 2015
• Authors: R Padmanaban, V. Muthukumaran, A. Vighnesh
• Keywords: AA1100, Friction Stir Welding, Response Surface Methodology, Tensile Strength

References

[1] Mishra, R.S. and Z.Y. Ma, Friction stir welding and processing. Materials Science and Engineering: R: Reports, 50(2005) 1-78.

[2] Nandan, R., T. DebRoy, and H.K.D.H. Bhadeshia, Recent advances in friction-stir welding - Process, weldment structure and properties. Progress in Materials Science, 53(2008) 980-1023.

DOI: 10.1016/j.pmatsci.2008.05.001

[3] Babajanzade Roshan, S., M. Behboodi Jooibari, R. Teimouri, G. Asgharzadeh-Ahmadi, M. Falahati-Naghibi, and H. Sohrabpoor, Optimization of friction stir welding process of AA7075 aluminum alloy to achieve desirable mechanical properties using ANFIS models and simulated annealing algorithm. The International Journal of Advanced Manufacturing Technology, 69(2013).

DOI: 10.1007/s00170-013-5131-6

[4] Amini, S., M.R. Amiri, and A. Barani, Investigation of the effect of tool geometry on friction stir welding of 5083-O aluminum alloy. The International Journal of Advanced Manufacturing Technology, 76(2015) 255-261.

DOI: 10.1007/s00170-014-6277-6

[5] Lotfi, A. and S. Nourouzi, Effect of Welding Parameters on Microstructure, Thermal, and Mechanical Properties of Friction-Stir Welded Joints of AA7075-T6 Aluminum Alloy. Metallurgical and Materials Transactions A, 45(2014) 2792-2807.

DOI: 10.1007/s11661-014-2235-z

[6] Saunders, N., M. Miles, T. Hartman, Y. Hovanski, S. -T. Hong, and R. Steel, Joint strength in high speed friction stir spot welded DP 980 steel. Int. J. Precis. Eng. Manuf., 15(2014) 841-848.

DOI: 10.1007/s12541-014-0407-9

[7] Reza-E-Rabby, M. and A.P. Reynolds, Effect of Tool Pin Thread Forms on Friction Stir Weldability of Different Aluminum Alloys. Procedia Engineering, 90(2014) 637-642.

DOI: 10.1016/j.proeng.2014.11.784

[8] Naga Malleswara Rao, G., Design optimization and analysis of a connecting rodusing ANSYS. International Journal of Science and Research., 2(2013) 225-229.

[9] Mao, Y., L. Ke, F. Liu, Q. Liu, C. Huang, and L. Xing, Effect of tool pin eccentricity on microstructure and mechanical properties in friction stir welded 7075 aluminum alloy thick plate. Materials & Design, 62(2014) 334-343.

DOI: 10.1016/j.matdes.2014.05.038

[10] Gandra, J., D. Pereira, R.M. Miranda, and P. Vilaça, Influence of Process Parameters in the Friction Surfacing of AA 6082-T6 over AA 2024-T3. Procedia CIRP, 7(2013) 341-346.

DOI: 10.1016/j.procir.2013.05.058

[11] Chiou, Y. -C., C. -T. Liu, and R. -T. Lee, A pinless embedded tool used in FSSW and FSW of aluminum alloy. Journal of Materials Processing Technology, 213(2013) 1818-1824.

DOI: 10.1016/j.jmatprotec.2013.04.018

[12] Padmanaban, R., A. Vignesh, V. MuthuKumaran, and S. Basil, A Study on Process Parameters and Tool Geometry Effect on Friction Stir Welding of AA1100. International Journal of Applied Engineering Research, 10(2015) 1266-1270.

[13] Myers, R.H. and D.C. Montgomery, Response Surface Methodology Process and product optimization using Designed Experiments. Second ed. John Wiley & Sons, Inc, 2001 Wiley Series in Probability and Statistics.

[14] Tansel, I., M. Demetgul, H. Okuyucu, and A. Yapici, Optimizations of friction stir welding of aluminum alloy by using genetically optimized neural network. The International Journal of Advanced Manufacturing Technology, 48(2010) 95-101.

DOI: 10.1007/s00170-009-2266-6