A Certifiable Machine Learning-Based Pipeline to Predict Fatigue Life of Aircraft Structures

The introduction of a machine learning-based pipeline for predicting the fatigue life of aircraft structures marks a significant advancement in aerospace safety. Traditional engineering methods, while reliable, are often labor-intensive and require extensive collaboration across multiple teams, which can delay critical safety assessments. This new approach leverages machine learning to streamline the prediction process, enabling quicker iterations and more efficient decision-making. By providing rapid estimates of fatigue life based on flight parameters, this pipeline not only enhances operational efficiency but also plays a vital role in early detection of fatigue cracks, thereby reducing the risk of in-flight failures. The validation of this method in realistic use cases further underscores its potential impact on the aerospace industry, aligning with ongoing efforts to integrate advanced technologies into safety-critical applications.