A leading challenge in the assembly process of aircraft skin panels is the precise control of part-to-part gaps to avoid excessive pre-tensions of the fastening element which, if exceeded, impair the durability and the response under dynamics loads of the whole skin assembly. The current practice is to measure the gap in specific points of the assembly with parts already at their final location, and then be-spoke shims are machined and inserted between the mating components to fill the gap. This process involves several manual measurement-fit-adjust quality loops, such as loading parts on the assembly frame, measuring gaps, off-loading parts, adding be-spoke shims and re-positioning parts ready for the fastening operation—as a matter of fact, the aircraft is re-assembled at least twice and therefore the current practice has been proved highly cost and time ineffective. Additionally, the gap measurement relies on manual gauges which are inaccurate and unable to follow the actual 3D profile of the gap. Taking advantage of emerging tools such as in-line measurement systems and large-scale physics-based simulations, this paper proposes a novel methodology to predict the part-to-part gap and therefore minimise the need for multiple quality loops. The methodology leverages a physics-driven digital twin model of the skin assembly process, which combines a physical domain (in-line measurements) and a digital domain (physics-based simulation). Central to the methodology is the variation model of the multi-stage assembly process via a physics-based simulation which allows to capture the inherent deformation of the panels and the propagation of variations between consecutive assembly stages. The results were demonstrated during the assembly process of a vertical stabiliser for commercial aircraft, and findings showed a significant time saving of 75% by reducing costly and time-consuming measurement-fit-adjust quality loops.
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