A Dynamic Prediction Method for Assembly Quality Based on Physics-Informed Machine Learning
A dynamic prediction method that integrates assembly deviation mechanisms and machine learning and can reduce the assembly out-of-tolerance rate by about 23%, providing a theoretical tool and technical support for high-precision aircraft assembly.