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Deep drawing is a widely employed technique for forming sheet metal in the packaging, home appliance, and automotive sectors. This method is crucial for mass production of varied forms, its purpose is to continuously enhance products while cutting costs. Nevertheless, it encounters numerous obstacles, such as springback, which is a deformation phenomenon that occurs when process parameters are not optimally chosen, and the need to optimize process parameters in order to minimize springback. The integration of Finite Element Simulation (FEM) and optimization techniques has made a substantial impact on cost reduction and enhanced product quality. The combination of FEM and optimization has led to promising outcomes. Hence, it is imperative to obtain a precise numerical model for accurately predicting springback in finite element simulations, as it is vital for optimization purposes. This study introduces a verified numerical model that accurately predicts springback, specifically for the Numisheet2011 Benchmark II. The model is utilized to analyze a 2D draw-bend method for the 'U-bend' issue, employing a 1.4mm thick DP780 steel plate. The behavior of DP780 steel is accurately described by the model, which incorporates Hill's anisotropic yield criterion and Swift's isotropic hardening model. The model's effectiveness was assessed by comparing its springback predictions with experimental results as a reference.
Aalouch et al. (2024) studied this question.