Trim allowance calculation and distribution optimization for aircraft skin panels based on complex assembly seam features measurement

In aerospace manufacturing, aircraft skin panels typically require manual secondary trimming prior to assembly to ensure appropriate assembly clearance, thereby meeting requirements for airtightness and structural safety. At present, the trimming process primarily relies on manual measurements and repeated trial-and-error fitting, involving frequent adjustments and multiple trimming operations. This process is inefficient, error-prone, and exhibits a low degree of digitalization. To address this issue, this paper proposes a digital trimming allowance computation and distribution optimization method for aircraft panels based on measuring complex assembly seam features, intending to advance digital trimming technologies for aerospace panel assembly, an area still lacking effective solutions. To tackle the challenge of measuring spatially closed seams under complex curvature conditions, a structure tensor and coordinate optimization-based optimal projection plane search strategy (STCPS) is introduced, along with a flexible seam measurement model (FSMM) to enable high-precision measurement of gap and flush features. In addition, a trimming allowance distribution optimization algorithm based on the trimming-aware coordinated strategy (TACS) is developed to address the low efficiency and quality issues caused by dispersed trimming allowances. Experimental results demonstrate that the proposed method significantly outperforms existing algorithms in terms of both accuracy and efficiency. Specifically, in the simulation environment, the mean measurement errors for gap and flush on eight types of model data are 4.9 μm and 5.8 μm, respectively; while on eight types of instance data the corresponding errors are 55.4 μm and 74.7 μm. The method achieves a mean trimming optimization rate of 96.84 % across 16 trimming scenarios, with a mean trim region reduction rate of 68.58 %. After intelligent planning of trimming segments, the trimming task volume is reduced by a mean of 40.55 %, and operational consistency is improved by an mean of 17.49 %. This study provides an effective technical solution and practical guidance for advancing the aerospace industry’s digital trimming and assembly processes.