الفهرس 
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Abstract
The present work was applied on 4 mm thick AA6061 aluminum
alloy sheets used in the construction of aircraft structures, such as wings
and fuselages, yacht construction, including small utility boats,
automotive parts. Simple tool pin and concave shoulder profile have
been manufactured and used in FSW of butt joints at different rotation
speeds, traveling speeds, and down force. The weld joints are evaluated
using visual inspection and macrostructure investigation, as well as
tensile and hardness testing.
The present work also investigates the prediction of the mechanical
properties of friction stir welding using the Artificial Neural Network
(ANN) in MATLAB program.
The experimental results were used to develop the mathematical
model. The combined influence of welding speed, rotation speed, and
axial force on the mechanical properties of 6061 T6 Al plates was
simulated. The Results of the tensile strength test were used to train and
test ANN. However, the main quality indicator of neural network has
generalization ability to predict accurately the output of unseen test data.
Verification of the numerical modeling was carried out by comparing
the simulation results to experimental data. The validation shows
agreement and satisfaction.