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Vers l’asservissement du pilotage en énergie d'une opération de forgeage : développement d'un métamodèle prédictif pour un jumeau numérique

Conférence invitée
Auteur
URIBE, David
ccBAUDOUIN, Cyrille
107452 Laboratoire de Conception Fabrication Commande [LCFC]
ccDURAND, Camille

URI
http://hdl.handle.net/10985/22880
Date
2022

Résumé

In the aeronautical sector, because parts are mainly of large dimensions and in high performance materials, products are forged in small batches. Forming these complex parts requires energy-controlled production means, such as screw presses or, more generally, forging hammer. With these machines, several successive strokes are necessary to obtain the parts desired geometry and mechanical characteristics. However, for these small quantities, the automation of the manufacturing process is not necessarily possible or profitable and consequently, the control of the machine remains dependent on the know-how of the operators, in particular with regard to the quantity of energy to be delivered blow after blow, the temperature, the lubrication conditions, etc. The main challenge is to provide flexibility and robustness particularly adapted to small batches, thus limiting the impact of process parameters variability on the part final quality. To reach that goal, the implementation of a digital twin is proposed. The objective of the project is to develop a digital twin in the context of forming materials on an energy-controlled screw press. The scientific challenge is to obtain an accurate, predictive and reactive twin that will allow real-time control of the process as well as access to information that cannot be measured during the manufacturing process. A methodology for the creation of a predictive meta-model based on a calibrated numerical simulation and updated by machine learning is proposed. This meta-model will compose the digital twin. Our approach is validated on a case study: the uni-axial compression of a copper cylinder. Finally, the following development phases of the digital twin are presented.

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  • Laboratoire de Conception Fabrication Commande (LCFC)

Documents liés

Visualiser des documents liés par titre, auteur, créateur et sujet.

  • Predictive control for a single-blow cold upsetting using surrogate modeling for a digital twin 
    Article dans une revue avec comité de lecture
    ccURIBE, David; ccBAUDOUIN, Cyrille; ccDURAND, Camille; ccBIGOT, Regis (Springer Science and Business Media LLC, 2023-12)
    In the realm of forging processes, the challenge of real-time process control amid inherent variabilities is prominent. To tackle this challenge, this article introduces a Proper Orthogonal Decomposition (POD)-based ...
  • Accurate real-time modeling for multiple-blow forging 
    Article dans une revue avec comité de lecture
    ccURIBE, David; ccDURAND, Camille; ccBAUDOUIN, Cyrille; ccBIGOT, Regis (Springer Science and Business Media LLC, 2024-10)
    Numerical simulations are crucial for predicting outcomes in forging processes but often neglect dynamic interactions within forming tools and presses. This study proposes an approach for achieving accurate real-time ...
  • Développement d’un jumeau numérique pour le pilotage en énergie d’une opération de forgeage 
    Article dans une revue sans comité de lecture
    URIBE, David; KRUMPIPE, Pierre; ccBAUDOUIN, Cyrille; ccDURAND, Camille (CIFORGE, 2022-06)
    Depuis plusieurs années, les processus de fabrication sont progressivement automatisés pour améliorer leur répétabilité et leur reproductibilité. Parallèlement, des optimisations sont apportées afin d’améliorer la robustesse ...
  • Towards the Real-Time Piloting of a Forging Process: Development of a Surrogate Model for a Multiple Blow Operation 
    Communication avec acte
    URIBE, David; ccDURAND, Camille; ccBAUDOUIN, Cyrille; KRUMPIPE, Pierre; ccBIGOT, Regis (Springer Nature Switzerland, 2023-08)
    Forging processes are defined by variables related to the workpiece, the tools, the machine, and the process itself, and these variables are called process variables. They have a direct impact on the quality of the finished ...
  • Real-time forging process control: integrating billet-related surrogate and machine behavior models 
    Article dans une revue avec comité de lecture
    ccURIBE, David; ccDURAND, Camille; ccBAUDOUIN, Cyrille; ccBIGOT, Regis (Springer Science and Business Media LLC, 2025-04)
    This study introduces a predictive surrogate model for real-time control in cold upsetting processes, incorporating both material and machine behaviors. Traditional approaches often simplify machine behavior as rigid or ...

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