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A new tailored solution to predict blow efficiency and energy consumption of hammer-forging machines

Article dans une revue avec comité de lecture
Auteur
MULL, Jean-François
ccBAUDOUIN, Cyrille
107452 Laboratoire de Conception Fabrication Commande [LCFC]
ccDURAND, Camille

URI
http://hdl.handle.net/10985/19656
DOI
10.1007/s00170-020-06237-2
Date
2020
Journal
International Journal of Advanced Manufacturing Technology

Résumé

Energy saving has become a real issue in process management and has led to the analysis of the energy consumption of forging machines, for the purpose of optimization. This study focuses on the amount of energy lost due to machine behaviour during the forming process. A spring-mass-damping model of the machine and tools system is associated with a billet model to describe hammer-forming operations only during the forging phase. Themodel parameters are identifiedwith experimental measurements of process variables during a stroke, providing parameters specifically adapted to the machine-tools system. Then, model predictions are validated by the experimental upsetting of steel and aluminium billets. The model accurately predicts forging process variables for consecutive blows with different materials. The decrease in process efficiency and the evolution from inelastic to elastic blows after several strokes on the same billet are also predicted by the model. This methodology provides a new, tailored solution that enables forging manufacturers to predict the forging energy consumption of their own machines. The approach developed in this work concerns gravity drop hammers but is also transferable to other energy-driven machines.

Fichier(s) constituant cette publication

Nom:
LCFC_IJAMT_2020_MULL.pdf
Taille:
1.680Mo
Format:
PDF
Fin d'embargo:
2021-04-01
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Documents liés

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  • Validation of a purely elastic model and a finite element model for a screw press 
    Communication avec acte
    MULL, Jean-François; ccDURAND, Camille; ccBAUDOUIN, Cyrille; ccBIGOT, Regis; ccBORSENBERGER, Marc (AIP Publishing, 2019-07)
    The increasing use of superalloys in the industry brings new issues to forging manufacturers concerning Finite Element analysis of the forming process. Once we consider high performing materials, significant differences ...
  • A FE Billet Model and a Spring-Mass-Damper Model for the Simulation of Dynamic Forging Process: Application to a Screw Press 
    Communication avec acte
    MULL, Jean-François; ccDURAND, Camille; ccBAUDOUIN, Cyrille; ccBIGOT, Regis (Springer International Publishing, 2021-07)
    In forging processes, the determination of blow efficiency is very important, as it quantifies the part of the stroke energy actually transmitted to the billet. Thus, forging processes should be deeply analyzed in order ...
  • Vers la modélisation d’une presse à vis : développement d’un modèle statique élastique 
    Communication avec acte
    ccDURAND, Camille; MULL, Jean Francois; ccBAUDOUIN, Cyrille; ccBIGOT, Regis (Association Française de Mécanique (AFM), 2019-09)
    The increasing use of superalloys in the forging industry induces the development of new manufacturing processes. These new processes are set up thanks to Finite Element simulation. But regarding the prediction of the ...
  • Instrumentation d’un procédé de forgeage : comparaison de différentes technologies de capteurs 
    Communication avec acte
    ccDURAND, Camille; FREUND, Ludovic; ccBAUDOUIN, Cyrille; ccBIGOT, Regis; GUÉRIN, Jean Dominique (S.MART (AIP PRIMECA), 2021-04)
    De nos jours, les simulations numériques sont de plus en plus utilisées dans l’industrie de la forge, et leur prédictibilité est validée grâce à des comparaisons avec des campagnes expérimentales. Il arrive cependant parfois ...
  • Comparison of different sensor technologies to monitor a forging process 
    Communication avec acte
    ccDURAND, Camille; FREUND, Ludovic; ccBAUDOUIN, Cyrille; ccBIGOT, Regis; GUÉRIN, Jean-Dominique (University of Liege, 2021-04)
    Nowadays, numerical simulations are more and more used in forging industry, and their predictability is validated through a comparison with experiments. But sometimes simulations and experiments provide significantly ...

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