A CFD-driven surrogate-based machine learning framework for multi-criteria quality optimization of family-mold processes
Published online on July 10, 2026
Abstract
Measurement and Control, Ahead of Print.
This study presents a machine learning-driven framework for the constrained multi-criteria optimization of family-mold processes, where the simultaneous production of geometrically dissimilar parts creates complex flow imbalances. Dimensional deformation (...
This study presents a machine learning-driven framework for the constrained multi-criteria optimization of family-mold processes, where the simultaneous production of geometrically dissimilar parts creates complex flow imbalances. Dimensional deformation (...