MICROSTRUCTURAL AND MECHANICAL ANALYSIS OF SHEET METAL BLANKING

Mounir TRABELSI, Boutheina BEN FRAJ, Hamdi HENTATI, Taoufik KAMOUN, Mohamed HADDAR

Abstract


The blanking test is performed under a variety of process parameters at various levels. Uncontrolled burr (Hbv) and the maximum blanking force (Fmax) is measured to predict the fracture mechanisms and to design tools. In this paper, design of experiments (DOE) and machine-learning (ML) methods were developed in order to predict Hbv and Fmax in blanking test. Hbv and Fmax are affected principally by the sheet thickness. Then, microstructural behavior is experimentally analyzed as function of sheet thickness. After that, series of experiment-based data into ML models training are elaborated to predict Hbv and Fmax. The proposed ML models, Random Forest (RF) and XGBoost (XGB), offer the best prediction of the output parameters.


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