Application of Adaptive Network Fuzzy Inference System to Die Shape Optimal Design in Sheet Metal Bending Process

Abstract

This paper combines adaptive network fuzzy inference system (ANFIS) and finite element method (FEM) to study the die shape optimal design in sheet metal bending process. At first, the explicit dynamic FEM is used to simulate the sheet metal bending process. After the bending process, the springback is analyzed by using the implicit static FEM to establish the basic database for ANFIS. Then, the die shape optimal design is performed by ANFIS using this database in the sheet metal bending process. As a verification of this system, the L-type and V-type dies are designed for the experiments to prove the reliability of FEM analysis and ANFIS optimal design by comparing the punch load and stroke relationship, the deformation history, stress distribution, and the bending angle of workpiece after springback between numerical and experimental results. It shows that a good agreement is achieved from comparison between numerical and experimental results. From this investigation, ANFIS has proved to be a useful scheme for die shape optimal design in the metal forming category.