A Combined Numerical and Experimental Investigation on Deterministic Deviations in Hot Forging Processes
- authored by
- Bernd Arno Behrens, Wolfram Volk, Daniel Maier, Lorenzo Scandola, Michael Ott, Kai Brunotte, Christoph Büdenbender, Michael Till
- Abstract
In hot forging processes, geometry of the formed workpieces deviate from the desired target geometry, due to complex interactions between tools and billets which result in inhomogeneous temperature and stress fields. The resulting deviation can only be mapped insufficiently by using numerical simulation which makes it difficult to be considered when designing the tool. Therefore, the development of forging tools requires an iterative adaptation process through a large number of revisions in the tool geometry, which escalates the resulting costs. To compensate the deviations and reduce the number of tool revisions, a holistic view of the influencing factors on the geometrical deviation is necessary. In order to address this issue, a hot forging process was developed, whose geometry is prone to high deviations, and a stress-based compensation model was applied. For this, forging experiments were carried out and a comparison was made between the actual geometry and the desired one by means of 3D coordinate measurements. The compensation methodology, which directly takes into account the complex 3D stress states during forming, allows to determine a compensating tool geometry. This opened up the possibility of validating the simulation results and testing a compensation model while eliminating deterministic deviations in hot forging processes.
- Organisation(s)
-
Institute of Metal Forming and Metal Forming Machines
- External Organisation(s)
-
Technical University of Munich (TUM)
- Type
- Conference article
- Journal
- Procedia Manufacturing
- Volume
- 47
- Pages
- 295-300
- No. of pages
- 6
- ISSN
- 2351-9789
- Publication date
- 26.04.2020
- Publication status
- Published
- Peer reviewed
- Yes
- ASJC Scopus subject areas
- Industrial and Manufacturing Engineering, Artificial Intelligence
- Electronic version(s)
-
https://doi.org/10.1016/j.promfg.2020.04.231 (Access:
Open)
-
Details in the research portal "Research@Leibniz University"