This is a preprint of a paper intended for publication in a journal or proceedings. Since changes may be made before publication, this preprint is made available with the understanding that it will not be cited or reproduced without the permission of the author. STER ~ .STBJBUTJON OF THJS OOCU MErJT lS U~lJMITED DISCLAIMER This report was prepared as an account of work sponsored by an agency of the United States Government.

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

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