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Effect of Welding Parameters and Artificial Aging on Mechanical Properties of Friction Stir Welded AA 7004 Alloys: Experimental and Artificial Neural Network Simulation

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Abstract

In this work, for the first-time effect of friction stir welding parameters (rotational and travel speeds) and artificial aging on mechanical properties of AA 7004 alloy is studied both experimentally and mathematically using artificial neural network. Microstructure, microhardness, yield and ultimate tensile strength of as welded and aged samples were evaluated. Artificial neural network model was used to predict the experimental results. The maximum strength of 341 MPa and joint efficiency of 80% was observed at 320 rpm and 1 mm/sec travel speed. Aging of as welded samples at 150 °C for 24 h resulted in increase in joint efficiency from 59 to 80% due to re-precipitation of precipitates in the weld zone. The samples welded at higher rotational and lower travel speeds show poor strength. This might be due to particle and grain coarsening. Outcome of the artificial neural network model results was found to be in good agreement with the experimental data.

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Acknowledgements

The authors would like to thank Defence Institute of Advanced Technology (DIAT), Pune for providing funding for this research work (No: DIAT/F/Adm/Project/OM/Mate/Corr).

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  1. Department of Metallurgical and Materials Engineering, Defence Institute of Advanced Technology, Pune, India

    A. Verma, B. Kotteswaran & T. Shanmugasundaram

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Verma, A., Kotteswaran, B. & Shanmugasundaram, T. Effect of Welding Parameters and Artificial Aging on Mechanical Properties of Friction Stir Welded AA 7004 Alloys: Experimental and Artificial Neural Network Simulation. Metallogr. Microstruct. Anal. 10, 515–524 (2021). https://doi.org/10.1007/s13632-021-00759-1

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