The design of ferritic steel welding alloys to fit the ever expected properties of newly evolved steels is not a very easy
task. It is traditionally attained by experimental trial and error, changing compositions and welding conditions until a sufficient
result is established. Savings in the economy and time might be achieved if the trial process could be minimised. The present
work outlines the use of an artificial neural network to model the elongation of ferritic steel weld deposits from their chemical
compositions, welding conditions and heat treatments.
