Digital Twin Virtual Welding Approach of Robotic Friction Stir Welding Based on Co-Simulation of FEA Model and Robotic Model

Abstract

Robotic friction stir welding has become an important research direction in friction stir welding technology. However, the low stiffness of serial industrial robots leads to substantial, difficult-to-measure end-effector deviations under the welding forces during the friction stir welding process, impacting the welding quality. To more effectively measure the deviations in the end-effector, this study introduces a digital twin model based on the five-dimensional digital twin theory. The model obtains the current data of the robot and six-axis force sensor and calculates the real-time end deviations using the robot model. Based on this, a virtual welding model was realized by integrating the FEA model with the digital twin model using a co-simulation approach. This model achieves pre-process simulation by iteratively cycling through the simulated force from the FEA model and the end displacement from the robot model. The virtual welding model effectively predicts the welding outcomes with a mere 6.9% error in lateral deviation compared to actual welding, demonstrating its potential in optimizing welding parameters and enhancing accuracy and quality. Employing digital twin models to monitor, simulate, and optimize the welding process can reduce risks, save costs, and improve efficiency, providing new perspectives for optimizing robotic friction stir welding processes.