Data-driven Metamodels for Failure Analysis of Power Electronic Modules
Published in 36th European Symposium on Reliability of Electron Devices, Failure Physics and Analysis (ESREF 2025), 2025
We present the results of using machine learning surrogate models to replace computationally expensive finite element simulations for estimating the remaining useful life of power electronic modules. This approach drastically accelerates the pipeline, achieving a 10⁶ computational speed-up while maintaining high precision with an R² score of 0.962.