An integration of RSM and ANN modelling approach for prediction of FSW joint properties in AA7178/AA5456 alloys

Jeyakrishnan, S.; Vijayakumar, S.; Naga Swapna Sri, M.; Anusha, P.

doi:10.1080/00084433.2024.2310344

Canadian Metallurgical Quarterly

2024

DOI: 10.1080/00084433.2024.2310344

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An integration of RSM and ANN modelling approach for prediction of FSW joint properties in AA7178/AA5456 alloys

S. Jeyakrishnan,

S. Vijayakumar,

M. Naga Swapna Sri

et al.

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2024

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Cited by 3 publications

References 51 publications

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Optimization of process parameters in 3D printing of polycarbonate for high heat applications

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Optimization of process parameters in 3D printing of polycarbonate for high heat applications

Srinivas,

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Artificial neural network approach for predicting the mechanical properties of Al7475/Flyash/SiC hybrid composite

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Wear parametric Optimization of FSW parameters on Al Alloy Using MLP technique

Cheepurupalli,

Selvaraj,

Reddy Muthadi

et al. 2024

E3S Web Conf.

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The purpose of this study was to identify the suitable Friction Stir Welding (FSW) parameters that would be used for welding scrapped Al alloy plates. On the experimental side, the study used four Factor Three-Level Full Factorial Design of Experiments (DoE) approach. Some of the input parameters incorporated in the analysis were the applied load, the sliding speed, displacement and weight percentage of Al2O3 reinforcement, and some of the output parameters were the specific wear rate and the coefficient of friction. The above said optimum parameters were established using the Minitab software while the above said experimental results was estimated using multilayer perceptron of the feed forward 4–10–1 network. For the actual test data set in the given experiment, the overall performance of the MLP predictions resulted to an R2. This results to a coefficient of determination (R R2 of 0.98474 and a mean squared error (MSE) of 0. 025075. Therefore the high R values, which are near to 1, show that the actual values mean and the predicted values mean are closely matched.

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An integration of RSM and ANN modelling approach for prediction of FSW joint properties in AA7178/AA5456 alloys

Cited by 3 publications

References 51 publications

Optimization of process parameters in 3D printing of polycarbonate for high heat applications

Optimization of process parameters in 3D printing of polycarbonate for high heat applications

Artificial neural network approach for predicting the mechanical properties of Al7475/Flyash/SiC hybrid composite

Wear parametric Optimization of FSW parameters on Al Alloy Using MLP technique

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