ESAFORM benchmark 2024: study on the geometric accuracy of a complex shape with single point incremental forming
M. Vanhulst, Youngrok Lee, Dennis Steinfels, Thomas Bremen, Konrad Perzyński, Hans Vanhove, Giuseppina Ambrogio, Radu-Eugen Breaz, Gianluca Buffa, Romina Conte, Luigi De Napoli, Livan Fratini, Xiao Da Terrence Fu, Francesco Gagliardi, Margarida F. Gralha, Putong Kang, Łukasz Kuczek, A. Senthil Kumar, Andreas Kunke, André Leonhardt, Yanle Li, Zhenwei Li, Roberto Licari, H. Long, Darren Wei Wen Low, Sever‐Gabriel Racz, Peter Scholz, M.B. Silva, Shaoqi Song, Dieter Weise, Krzysztof Żaba, Hui Zhu, David Bailly, Mihaela Banu, Łukasz Madej, Joost R. Duflou
Abstract
The benchmark 2024 project on Incremental Sheet Forming (ISF), involving 15 research institutes in 13 experimental contributions, provided a unique opportunity to compare experimental outputs from various setups and forming strategies in ISF. This collaboration led to the development of uniform data exchange formats, measurement guidelines, and standardized nomenclature, fostering efficient future collaborations. The project addressed challenges in geometric accuracy when forming a relatively large part (400 × 400 mm) using Single Point Incremental Forming (SPIF) and focused on multiple common pitfalls in ISF, in particular the tent effect and pillow effect. Additionally, some experiments have been conducted using Two Point and Double Sided Incremental Forming (TPIF and DSIF). By combining the knowledge and experience of all participating institutes, this project aimed to provide insights into effective parameter choice and toolpath strategies, and shows the importance of multi-stage processes to increase the geometric accuracy. Despite the theoretical simplicity of SPIF setups, such multi-stage toolpath strategies directed toward improved geometric accuracy also add some new challenges. The study highlighted the need for multi-stage strategies that focus on local effects, as well as geometric compensation techniques to enhance ISF's industrial applicability. Alternative process variants like TPIF and DSIF, showed promising results, but they also had limitations and presented challenges, emphasizing the importance of predictive simulation tools to further increase geometric accuracy. The scalability of ISF experiments remains a significant challenge, necessitating further research into scale laws for process optimization.