The objective of this work was to investigate the
mechanical properties in order to demonstrate the
feasibility of friction stir welding for joining Al 6061
aluminum alloy welding was performed on pipe with
different thickness 2 ,3 and 4mm,five rotational speeds
(485,710,910,1120 and1400) RPM and a traverse speed
(4,8 and 10)mm/min was applied. This work focuses on
two methods such as artificial neural networks(ANN)
using software (pythia) and response surface
methodology (RSM) to predict the tensile strength, the
percentage of elongation and hardness of friction stir
welded 6061 aluminum alloy. An artificial neural
network (ANN) model was developed for the analysis of
the friction stir welding parameters of Al 6061aluminum
pipe. The tensile strength, the percentage of elongation and
hardness of weld joints were predicted by taking the
parameters Tool rotation speed, material thickness and
travel speed as a function. A comparison was made
between measured and predicted data. Response surface
methodology (RSM) also developed and the values
obtained for the response Tensile strengths, the
percentage of elongation and hardness are compared
with measured values. The effect of FSW process
parameter on mechanical properties of 6061 aluminum
alloy has been analyzed in detail