Sub-Project 4(Yeong-Do Park): Development of Autonomous Process Parameter Correction System for Resistance Spot Welding (RSW)

Key Research Activities

• Real-time collection of key process signals such as dynamic resistance, current, and electrode force during the welding process, and construction of a systematic database
• Identification of key process variables that determine quality through correlation analysis between real-time monitoring data and welding quality
• Quantification of quality grades based on surface and internal defect data detected through non-destructive testing (ultrasonic, etc.) and performing labeling for AI training
• Advancement of predictive technology to prevent welding defects in advance by detecting microscopic variations or quality deviations occurring during the process in real-time
• Implementation of an automatic correction logic that optimizes current, welding time, and electrode force in real-time by analyzing the deviation between AI prediction results and actual process signals