Application Of Artificial Neural Network In Predicting The Weld Quality Of A Tungsten Inert Gas Welded Mild Steel Pipe Joint

ABSTRACT The weld quality of Tunston inert gas welded joint has been investigated to identify the most economical weld parameters that will bring about optimum properties. Artificial neural network has been used in the prediction and optimization of the Tunston inert gas weld of mild steel pipes. Neural network model was generated using the Levenberg-Marquardt algorithm with feed ward back propagation learning rule. Results show that the generated neural network model was able to predict tensile and yield strength to a mean square error of 34.2.