## 1 Introduction  
The accurate prediction of mechanical behavior in sheet-metal components is crucial for the design and validation of safety-critical structures in industries such as transportation, automotive, and aerospace [1, 2]. Since simulations with Finite Element Method (FEM) can accurately model complicated geometries and loading conditions, they are frequently used for this purpose [3, 4]. However, traditional FEM models assume homogeneous material properties, failing to implement the local variations that occur during manufacturing processes such as stamping [5]. This simplification causes discrepancies between simulated and experimental results, particularly for components with large deformations and complex loading scenarios [6, 7, 8, 9]. In fact, sheet-metal stamping introduces significant non-uniformities in mechanical properties, including localized thinning, strain hardening, and anisotropy [10, 11, 12, 13], which can impact the structural performance of the component, especially under high loads where yield strength and thickness variations play a crucial role [14, 15, 16]. Nonlinear FEM has proven to be accurate, offering the capability to account for anisotropy and yield criteria, and to model the springback phenomenon [17]. There are also many studiesinvestigating the different types of plane stress and strain in sheet-metal forming. [PERSON] et al. [18] analyzed the ductile fracture of thin metal plates, showing that fracture strain is significantly higher in plane strain bending than in far-field tension due to differences in localization mechanisms and stress states, with implications for material design and predictive modeling. [PERSON] et al. [19] investigates the potential of metal forming processes not only to shape products but also to predict and control their mechanical and physical properties throughout the manufacturing chain. The paper highlights how advancements in analytical and measurement techniques allow for accurate prediction and deterministic setting of properties such as hardness, residual stress, formability, and anisotropy during forming processes. [PERSON] et al. [20] introduced a Lode-dependent anisotropic-asymmetric hardening model (LAA-Yld91) for metals to precisely characterize anisotropic hardening and tension-compression asymmetry under diverse loading conditions. By coupling two Yld91 anisotropic functions with a Lode-dependent weight function and optimizing parameters via a neural network, the model demonstrates high accuracy in predicting yield surface evolution for various alloys, including Ti-6 Al-4V, DP980, and AA 5754-O, with applications in advanced metal forming simulations. A detailed study on simple shear tests demonstrates their effectiveness in characterizing the plastic anisotropy of rolled metal sheets under large strains. By optimizing specimen geometry and clamping techniques, the research improves stress and strain homogeneity, leading to more accurate evaluations of anisotropic hardening behavior essential for constitutive modeling and forming process simulations [21]. [PERSON] and [PERSON] [22] emphasized the significance of a systematic approach that integrates experimental methods with FEM analysis to determine material properties under large strains. In fact, sheet-metal subjected to plastic deformation during stamping is not characterized by uniform properties due to the inherent anisotropies introduced during the rolling process of the sheet. The study calibrates the parameters of a non-quadratic yield function, which is subsequently used to enhance the accuracy of tensile test simulations. [PERSON] et al. [23] examine the impact of anisotropy on the vibration behavior of S600 Mc sheet-metal, highlighting its importance in plastic deformation simulations. Their study combines experimental vibration tests at various orientations with finite element analysis, demonstrating the influence of anisotropy on structural damping and its implications for high-cycle fatigue performance.