Abstract
This study presents a predictive modeling approach for the resistance spot-welding (RSW) process of 1.2-mm-thick spot-welded sheets made of the third-generation advanced high-strength steel (3G-AHSS) known as 980HF steel. The study aims to ascertain the effect of predetermined welding process parameters on welding performance. The investigation considered welding parameters such as welding current, welding time, electrode force, and holding time. On the basis of the peak load, absorbed energy, microhardness, and microstructural characteristics, the quality of the RSW performance was evaluated. The Central Composite Design (CCD) of the Response Surface Method (RSM) was employed as a popular predictive modeling technique. The design of the experiment (DoE) approach was utilized to construct the CCD. The RSM model demonstrated high prediction accuracy with an efficiency of 98% for the peak load and 95% for the absorbed energy. The validity of the predictive model was confirmed through supplementary experiments, which accounted for 20% of the total designed experiments used in creating the model. The supplementary experiments involved randomly selected welding parameters within the predetermined welding process parameters range. The validation study indicated model efficiencies of 85.44% for the peak load and 81.84% for the absorbed energy. Microhardness measurements taken across the weld identified distinct zones, with an average microhardness value of 320 HV for the base metal (BM), 310 HV for the sub-critical heat-affected zone (SCHAZ), 400 HV for the intercritical heat-affected zone (ICHAZ), 550 HV for the upper critical heat-affected zone (UCHAZ), and 516 HV for the fusion zone (FZ). Overall, the results demonstrated the capability of the RSM model to predict the welding performance, thereby reducing the need for extensive experimental investigations, which save time and resources.
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The authors gratefully acknowledge the support provided by the Mechanical Engineering Department at the University of Benghazi and the CAMJ group at the University of Waterloo for facilitating the microhardness and SEM analyses.
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Elhemri, M.N., Elmabrouk, O., Haidar, F. et al. Modeling and Prediction of a 3G-980HF Spot Weld Shear Strength Using Response Surface Methodology. Metallogr. Microstruct. Anal. (2024). https://doi.org/10.1007/s13632-024-01057-2
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DOI: https://doi.org/10.1007/s13632-024-01057-2