J. Heinisch

Process control strategies for injection molding processes with changing raw material viscosity

C. Hopmann, J. Heinisch, 2017 .

Comparison of design of experiment methods for modeling injection molding experiments using artificial neural networks

C. Hopmann, J. Heinisch, Yannik Lockner, 2021 .

Combined learning processes for injection moulding based on simulation and experimental data

Tobias Meisen, Sabina Jeschke, Christian Hopmann, 2019, PROCEEDINGS OF PPS-33 : The 33rd International Conference of the Polymer Processing Society – Conference Papers.

Quality Control in Injection Molding based on Norm-optimal Iterative Learning Cavity Pressure Control

D. Abel, C. Hopmann, J. Heinisch, 2020, IFAC-PapersOnLine.

Self-optimizing Production Technologies

Wolfgang Schulz, Fritz Klocke, Robert Schmitt, 2017 .

Interdisciplinary Data Driven Production Process Analysis for the Internet of Production

Gerhard Lakemeyer, Tobias Meisen, Sabina Jeschke, 2018 .

Transfer-Learning: Bridging the Gap between Real and Simulation Data for Machine Learning in Injection Molding

Tobias Meisen, Thomas Thiele, Christian Hopmann, 2018 .

Cross-phase Model-based Predictive Cavity Pressure Control in Injection Molding

Christian Hopmann, Dirk Abel, Sebastian Stemmler, 2019, 2019 IEEE Conference on Control Technology and Applications (CCTA).