The pre-form design in hydroforming process plays a key role in improving product quality, such as defect-free property and proper final product. This approach, however, leads not only to the increase of significant tool cost but also to the extended down-time of the production equipment. It is thus necessary to reduce time and man power through an effective method of pre-form design. In this paper, the equi-potential lines designed in the electric field are introduced to find an appropriate pre-form shape. The equi-potential lines generated between two conductors of different voltages show similar trends for minimum work paths between the undeformed shape and the deformed shape. Based on this similarity, the equi-potential lines obtained by arrangement of the initial and final shapes are utilized for the design of the pre-form, and then the finite element simulations are done for finding the forming pressure of each pre-form shape. Finally, the pre-form and its corresponding forming pressure with other parameters are used for training an artificial neural network. This trained neural network can be used for estimating the proper pre-form shape and forming pressure for a SUS304 tube inside an square die or other configurations of die (Geometrical shape) and tube (Diameter and thickness).

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