TY - JOUR A1 - Wagner, Marcus A1 - Franke, Markus A1 - Krause, Tom Janis A1 - Heinle, Ingo T1 - Data augmentation of material properties for machine learning in industrial production - a case study in an automotive press shop JF - Engineering Computations : International journal for computer-aided engineering and software N2 - In the context of industrial production, the utilisation of data recording and processing techniques is becoming increasingly prevalent across the manufacturing sector. The solutions integrate sensors, facilitate the transmission of data, and enable data-driven decision-making, thereby reducing downtime and optimising quality. However, challenges emerge due to the limited non-transferable data or models between processes. Alterations to the production process can render collected data invalid, resulting in restricted datasets and potential overfitting. To address these issues, techniques such as data augmentation are employed. This study aims to develop a data augmentation methodology applicable in dynamic, data-scarce production environments, enhancing the robustness of regressor predictions. KW - Data augmentation KW - Machine learning KW - Manufacturing KW - Deep drawing Y1 - 2025 U6 - https://doi.org/10.1108/EC-08-2024-0787 PB - Emerald Publishing CY - Leeds ER -