Optimization and prediction of heat input of mild steel weldment, using genetic algorithm

In welding materials, the purpose is to resist the variation of the microstructure of the material and retain the mechanical properties and the chemical properties. Most welded joint fail due to the utilization of poor welding process. This poor welding process produces a minimum heat input that could cause insufficient melting of the electrode, insufficient melting of the electrode is responsible for inadequate penetration of liquid metal into the welded joint. Literature has shown that produced welded joints by insufficient penetration of the liquid metal have low bearing capacity. This indicates that such welded joints would not be able to sustain the design load. In order to achieve deep liquid metal penetration, optimizing and prediction of heat input of mild steel weldment, utilizing genetic algorithm is studied. The purpose of this study therefore is to develop models that would minimize the heat input. Genetic Algorithm which imitates the evolution progression and functions on the principle of the natural theory choice with evolution was utilized for the result analysis. It was shown as a result that combination of welding time 79.15 sec current of   239.03 A welding speed of  56.59 mm/s  voltage of  29.87 v feed rate of  130 mm/s will produce optimal heat input of 117.30 KJ