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Abstract. The characterization of sheet metal behavior is of utmost importance for the accurate virtualization of sheet metal forming processes. Newly proposed mechanical testing approaches are overcoming the use of standard mechanical tests. Test configurations with more complex geometries present richer mechanical fields and, therefore, provide a higher quantity of valuable information about the material behavior in a more efficient manner. To extract that information, full-field measurement techniques such as Digital Image Correlation are being used. Although several test designs have already been proposed, the choice of the best one to calibrate a chosen mechanical model is still an issue. This work aims at proposing Key Performance Indicators (KPIs) that are able to rank mechanical tests by their potential to enhance the material behavior characterization process. These metrics evaluate quantitatively the quality and the importance of the data that each test can provide. The potential of three test designs to characterize accurately sheet metal mechanical behavior is analyzed using the proposed KPIs. From a uniaxial tensile loading test up to rupture, the numerical mechanical information is extracted, and the performance of each test is evaluated and compared.

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