Optimization of the nosing process of metal pipe using genetic algorithm

percentage of nosing is expressed based on the effective parameters, and finally, the optimal percentage of nosing for the regression equation obtained by the genetic algorithm is obtained. percentage was determined by the experimental design method. In this research, response level method and central composite design were used. Variance analysis method is used to check the relationship between output variables and input parameters. The results show that as the wall slope increases, the percentage of nosing increases and as the thickness and friction coefficient increase, the percentage of nosing decreases. It can also be seen that, to increase the percentage of nosing, the slope of the wall should be high and the friction coefficient should be low. Also, by using the genetic algorithm and optimizing the regression equation obtained from the analysis of variance, the maximum percentage of nosing has been obtained at 60.81.