Kristian Kersting

Requirements for numeric models as sources of synthetic data for predicting real-world data sets in progressive deep drawing processes

Abstract In the field of forming technology, synthetic data generated by finite element (FE) simulations is increasingly being used to train machine learning (ML) models for part quality prediction. However, the predictive accuracy on real-world process data is often limited by t...