Optimization of roll forming process with evolutionary algorithm for green product

摘要: Knowledge-Based Neural Network model is known as one of the most useful methods which can predict every single variability to create process parameters for data on Roll Forming process. To get best quality product and in roll forming, has be trained with high reliability. obtain target aimed, this paper proposes a new novel optimal algorithm training integration between Genetic Algorithm Hill Climbing Algorithm. Initially, global optimization method carried out find optimum area by using Algorithm, then climbing will effectively detect positions that local region accuracy model. Additionally, set model, Finite Element Analysis result fidelity Model used. From results simulation, we efficiency proposed higher than conventional forming