Dynamic modelling of a servo self-pierce riveting (SPR) process

Self-pierce riveting (SPR) is a complex joining process where multiple layers of material are joined by creating mechanical interlock via the simultaneous deformation inserted rivet and surrounding material. Due to large number variables which influence resulting joint, finding optimum parameters has traditionally posed challenge in design process. Furthermore, there gap knowledge regarding how changes made system may affect produced joint. In this paper, new system-level model an inertia-based SPR proposed, consisting physics-based machine empirically-derived Model predictions validated against extensive experimental data for sets input conditions, defined setting velocity, motor current limit support frame type. The dynamics head height joint predicted high level accuracy. Via model-based case study, identified, enable either cycle time or energy consumption be substantially reduced without compromising overall quality predictive capabilities leveraged reduce costs involved validation systems processes.