Process optimization of robust bonding between DP590 and AA6061 using resistance riveting welding

Abstract

The process of resistance riveting welding (RRW) has the potential to be a cost-effective and efficient method for joining dissimilar materials. However, the impact of process parameters on the mechanical properties of the joints is not well understood. To address this issue, the study proposed an optimization method to maximize the cross tensile peak load and tensile shear peak load of the joint. A total of 54 experiments were conducted with different process parameters. Cross tensile and tensile shear tests of the joints were conducted, and then the cross-sectional morphology and microstructure of the joints and the intermetallic compounds at the interface were observed. And finally the fracture morphology of the joints was analyzed. The results showed that the total heat input and heat input per unit time were the main factors affecting the joint properties. Then a process optimization model based on a combination of snake optimization algorithm, support vector regression model, and multi-objective optimization Grey Wolf algorithm was established. The established optimization model was experimentally validated and found to be effective in quickly establishing an accurate prediction and optimization model for the RRW process. This study provides important technical guidance for the application of the RRW process and the utilization of the optimization model in other industrial scenarios.