Optimization of MIG welding parameters using Artificial Neural Network (ANN) and Genetic Algorithm (GA)

There are many mathematical models by which we can control the quality of weld properties in welding. We can use neural network which express some relationship between input and output. Now a days neural network is very useful tool by which we can interrelate input and output parameters compare it with that of the value which is given by the neural network and we can optimize the value. An artificial neural network and genetic algorithm is use to optimize the parameter. An Artificial Neural Network is a mathematical model inspired by biological neural networks. Here we are using ANN model for MIG (metal inert gas welding) welding. Two dissimilar type of work piece (stainless steel grade 304 and stainless steel grade 316) was taken and the welding experiment was performed and the result was analyse by using artificial neural network and genetic algorithm and it was find that ANN was given the batter result argon was taken as shielding gas and experiment was done on full factorial. Genetic Algorithm (GA) used to optimize the value of output. And it is concluded that Artificial Neural Network (ANN) successfully integrated as other regression model.