Study on the factors affecting springback and the application of data mining in springback analysis
Springback of sheet metal induced by elastic recovery is one of major defects in sheet metal forming processed. Springback is influenced by many factors including properties of the sheet material and processing conditions. In this paper, springback simulation is conducted and comparisons between results based on different processing variables are illustrated. Furthermore, the discovery of knowledge of the effects of geometry and process parameters on springback from FEM results becomes increasingly important, as the number of numerical simulation has grown exponentially. Data mining is an effective tool to realize knowledge discovery in simulation results. In the present paper, a data-mining algorithm, rough sets theory (RST), is applied to analyze the effects of process parameters on springback in U-bending.