Neural network-based estimation and compensation of friction for enhanced deep drawing process control

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Authors

Fluctuating process conditions, such as lubrication, can disturb the production process and lead to faulty components that have cracks or wrinkles. Real-time identification of process parameters can detect deviations in sheet forming operations and enable the process parameters to be adjusted. To increase process robustness, closed-loop control is often used to monitor and influence the material draw-in, which corresponds to the material flow and can be measured by camera systems inside the deep-drawing press. The aim of this work is to develop a control concept that can predict the optimum blank holder force by estimating the coefficient of friction based on the material draw-in of the last stroke. Using a cross-die geometry, it is shown how the material draw-in can be determined experimentally by means of a camera system and numerically by FE simulations. Finally, artificial neural network-based models are trained through simulations and are subsequently tested on a numerical case study in which the coefficient of friction is changed as a disturbance variable and must be compensated for. The widely applicable control concept has the potential to incorporate additional softsensors, for example to determine material properties, and other target variables, such as the punch force, into the optimization algorithm.
OriginalspracheEnglisch
TitelMaterial Forming ESAFORM 2024 : The 27th International ESAFORM Conference on Material Forming – ESAFORM 2024 – held in Toulouse (France), at the Pierre Baudis Convention Center between 24-26th April, 2024
HerausgeberAnna Carla Araujo, Arthur Cantarel, France Chabert, Adrian Korycki, Philippe Olivier, Fabrice Schmidt
Anzahl der Seiten10
ErscheinungsortMillersville
VerlagMaterialsResearchForum LLC
Erscheinungsdatum15.05.2024
Seiten1462-1471
Aufsatznummer162
ISBN (Print)9781644903131
ISBN (elektronisch)978-1-64490-313-1
DOIs
PublikationsstatusErschienen - 15.05.2024
Veranstaltung27th International ESAFORM Conference on Material Forming - ESAFORM 2024 - Pierre Baudis Convention Center, Toulouse, Frankreich
Dauer: 24.04.202426.04.2024
Konferenznummer: 27
https://esaform24.fr/

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