Enhancing metal-forming predictions with VR-infused digital twin models

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Enhancing metal-forming predictions with VR-infused digital twin models

URIBE David, BAUDOUIN Cyrille, LOCARD Yoan, DURAND Camille, BIGOT Régis

Abstract. This article presents a two-step method to enhance metal-forming predictions by integrating Virtual Reality (VR) into Digital Twin models, focusing on single-blow cold copper upsetting operations. The process begins with developing a real-time predictive surrogate model that considers actual process parameters, acting as a crucial link between conventional numerical simulations and immediate decision-making. Subsequently, the surrogate model is integrated into a realistic VR environment, aligned with the experimental forging setup. The study underscores the need and potential advantages of real-time digital twins in the forging field, emphasizing the bridging capability between numerical simulations and instant decision-making through predictive modeling and immersive virtual environments.

Keywords
Digital Twin, Virtual Reality, Forging Process, Surrogate Model, Numerical Simulation

Published online 4/24/2024, 11 pages
Copyright © 2024 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: URIBE David, BAUDOUIN Cyrille, LOCARD Yoan, DURAND Camille, BIGOT Régis, Enhancing metal-forming predictions with VR-infused digital twin models, Materials Research Proceedings, Vol. 41, pp 2309-2319, 2024

DOI: https://doi.org/10.21741/9781644903131-254

The article was published as article 254 of the book Material Forming

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

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