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Prediction and Experimental Validation of Peak Temperature in Friction Stir Welded AA2024 with AA5083 by Response Surface Methodology


Affiliations
1 Department of Mechanical, Karunya Institute of Technology and Sciences, Coimbatore – 641114, Tamil Nadu, India
 

Objective: The work aims at prediction of the peak temperature using Response Surface Methodology. Methods/ Statistical Analysis: Dissimilar Aluminum Alloys AA2024 and AA5083 O were friction stir welded. A fifteen run 3 factorial 3 level Box Behnken design was conducted and temperature generated were measured at both sides of the alloys. Thermocouples were employed for the same. The temperature was recorded and studies conducted. Response surface plots were used to obtain the peak temperature and effect of various parameters. Findings: The relationship between the process parameters and the temperature were established using ANNOVA. Mathematical models were development which can apply for future predictions. The traverse speed, rotational speed and the tool profile contributed to the temperature generation. The peak temperature was obtained at 1200 rpm, 25 m/min and threaded cylindrical tool pin profile. Application/Improvements: The temperature at the re-treating side was recorded to be higher compared to the advancing side.
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  • Jagathesh K, Jenarthanan MP, Babu PD, Chanakyan C. Analysis of factors influencing tensile strength in dissimilar welds of AA2024 and AA6061 produced by friction stir welding. Journal of Australian Journal of Mechanical Engineering. 2017; 15(1):19–26. https://doi.org/10.1080/14 484846.2015.1093229
  • Eberl I, Hantrais C, Ehrtsrom JC, Nardin C. Friction stir welding dissimilar alloys for tailoring properties of aerospace parts. Journal of Science and Technology of Welding and Joining. 2010; 15(8):699–705. https://doi.org/10.1179/136217110X12813393169499
  • DebRoy T, Bhadeshia HKDH. Friction stirs welding of dissimilar alloys – a perspective. Journal of Science and Technology of Welding and Joining. 2010; 15(4):266–70. https://doi.org/10.1179/174329310X12726496072400
  • Tavares SMO, Castro RAS, Richter-Trummer V, Vilaca P, Moreira PMGP, de Castro PMST. Friction stirs welding of T-joints with dissimilar aluminum alloys: Mechanical joint characterization. Journal of Science and Technology of Welding and Joining. 2010; 15:312–8. https://doi.org/10.1 179/136217109X12562846839114
  • Guo JF, Chen HC, Sun CN, Bi G, Sun Z, Wei J. Friction stir welding of dissimilar materials between AA6061 and AA7075 Al alloys effects of process parameters. Materials and Design (1980-2015). 2014; 56:185–92.
  • Hussein SK. Analysis of the temperature distribution in friction stir welding of AA 2024-T3 and AA 6061-T6 using finite element method. U.P.B Science Bulletin. 2016; 78(4):119–32.
  • De Backer J, Bolmsjo G. Thermoelectric method for temperature measurement in friction stirs welding. 2013; 18:558–65.
  • Zhang Z, Zhang HW. Numerical studies of preheating time effect on temperature and material behaviours in friction stir welding process. Journal of Science and Technology of Welding and Joining. 2007; 12:436–48. https://doi.org/10.1179/174329307X214386
  • Tutum CC, Deb K, Hattel JH. Multi-criteria optimization in friction stir welding using a thermal model with prescribed material flow. Journal of Materials and Manufacturing Processes. 2013; 28:816–22. https://doi.org/10.1080/10426914.2012.736654
  • Soundararajan V, Zekovic S, Kovacevic R. Thermo-mechanical model with adaptive boundary conditions for friction stirs welding of Al 6061. International Journal of Machine Tools and Manufacture. 2005; 45(14):1577–87. https://doi.org/10.1016/j.ijmachtools.2005.02.008
  • Khandkar MZH, Khan JA, Reynolds AP. Prediction of temperature distribution and thermal history during friction stir welding: Input torque based model. Science and Technology of Welding and Joining. 2003; 8:165–74. https://doi.org/10.1179/136217103225010943
  • Verma S, Meenu, Misra JP. Study on temperature distribution during friction stir welding of 6082 aluminum alloy. Materials Today: Proceedings. 2017; 4:1350–6. https://doi.org/10.1016/j.matpr.2017.01.156
  • Bisadi H, Rasaee S, Farahmand M. Experimental study of the temperature distribution and microstructure of plunge stage in friction stir welding process by the tool with triangle pin. Archives of Civil and Mechanical Engineering. 2014; 61(3):483–93. https://doi.org/10.2478/meceng-2014-0028
  • Bindu KDB, Trivedi PAM. Effect of size of tool on peak temperature and viscosity during friction stir welding of AA6061-T6 aluminum alloy using hyper works. International Journal of Innovative Research in Science, Engineering. 2013; 2:914–9.
  • Hao DD, Tra TH, Hoa VC. Study of effect of friction stir welding parameters on impact energy of AA7075-T6. Tạpchi Khoa hocva Congnghe. 2016; 54(1):99–108.

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  • Prediction and Experimental Validation of Peak Temperature in Friction Stir Welded AA2024 with AA5083 by Response Surface Methodology

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Authors

R. Raja
Department of Mechanical, Karunya Institute of Technology and Sciences, Coimbatore – 641114, Tamil Nadu, India
Sabitha Jannet
Department of Mechanical, Karunya Institute of Technology and Sciences, Coimbatore – 641114, Tamil Nadu, India
D. Emmanuel Sam Franklin
Department of Mechanical, Karunya Institute of Technology and Sciences, Coimbatore – 641114, Tamil Nadu, India

Abstract


Objective: The work aims at prediction of the peak temperature using Response Surface Methodology. Methods/ Statistical Analysis: Dissimilar Aluminum Alloys AA2024 and AA5083 O were friction stir welded. A fifteen run 3 factorial 3 level Box Behnken design was conducted and temperature generated were measured at both sides of the alloys. Thermocouples were employed for the same. The temperature was recorded and studies conducted. Response surface plots were used to obtain the peak temperature and effect of various parameters. Findings: The relationship between the process parameters and the temperature were established using ANNOVA. Mathematical models were development which can apply for future predictions. The traverse speed, rotational speed and the tool profile contributed to the temperature generation. The peak temperature was obtained at 1200 rpm, 25 m/min and threaded cylindrical tool pin profile. Application/Improvements: The temperature at the re-treating side was recorded to be higher compared to the advancing side.

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DOI: https://doi.org/10.17485/ijst%2F2018%2Fv11i44%2F131757