Optimum Designing of Forging Preform Die for the H-shaped Parts Using Backward Deformation Method and Neural Networks Algorithm

محورهای موضوعی : Manufacturing process monitoring and control

Afshin Naeimi ¹ , Mohsen Loh Mousavi ² , Ali Eftekhari ³

1 - MSc. Student of Department of Mechanical Engineering, Islamic Azad University of Khomeini Shahr.
2 - Assistant Professor, School of Engineering, Department of Mechanical Engineering, Islamic Azad University of Khomeini Shahr
3 - Assistant Professor, School of Engineering, Department of Mechanical Engineering, Islamic Azad University of Khomeini Shahr.

تاریخ دریافت : 1394/04/14 تاریخ پذیرش : 1394/04/14 تاریخ انتشار : 1393/05/10

کلید واژه: Artificial Neural Network, ABAQUS, Forging Preform Die, Backward Deformation Method,

چکیده مقاله :

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 H-shaped 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.