Title of article :
Optimum Designing of Forging Preform Die for the H-shaped Parts Using Backward Deformation Method and Neural Networks Algorithm
Author/Authors :
Naeimi, Afshin Department of Mechanical Engineering - Islamic Azad University of Khomeini Shahr , Loh Mousavi, Mohsen Department of Mechanical Engineering - Islamic Azad University of Khomeini Shahr , Eftekhari, Ali Department of Mechanical Engineering - Islamic Azad University of Khomeini Shahr
Abstract :
In a closed die forging process, it is impossible to form complex shapes in one stage, and thus it becomes necessary to use preform dies. In the present study, Backward Deformation Method and FE simulation via ABAQUS software has been used in order to design preform die of the Hshaped parts. In the Backward Deformation Method, the final shape of the part is considered as a starting point and using a specific method, a plastic returning path is predicted. Afterwards, using
FE results obtained by simulation of the forging process, an artificial neural network is designed to predict the material behavior under various conditions and for different kinds of preform to select optimum preform dies.
Keywords :
Artificial Neural Network , ABAQUS , Backward Deformation Method , Forging Preform Die
Journal title :
Astroparticle Physics
