Relevant material characterization for load prediction in incremental forming - Laboratoire de Génie Civil et Génie Mécanique Accéder directement au contenu
Article Dans Une Revue International Journal of Material Forming Année : 2022

Relevant material characterization for load prediction in incremental forming

Résumé

Robotic incremental sheet forming has arisen a recent industrial interest, as a more flexible and cost-effective solution to the process using rigid computer numerical control (CNC) machines. However, the numerical prediction of the forming loads and final geometry coupled to an elastic modeling of the robot is essential to optimize the robot trajectory and thus to ensure the geometrical accuracy of the final part. Within this context, the aim of this study is to investigate the accuracy of the load prediction in the case of a single point incremental forming process of a commercially pure (CP) titanium alloy sheet. The mechanical behavior is characterized at room temperature under two strain states, i.e., uniaxial and biaxial tension, and a truncated cone of the same material is obtained by single point incremental forming. A 3D cell records all the components of the applied load during the forming and the part is laser scanned at the end of the process, though still clamped along the outer edge. A numerical model of the process is developed assuming some symmetries to reduce the computational time. The influence of the hardening law, either identified from the uniaxial or biaxial tensile tests, on the forming load prediction is investigated, with a focus on the strain path during single point incremental forming.
Fichier principal
Vignette du fichier
Article_aab_HAL.pdf (2.63 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03631021 , version 1 (25-07-2022)

Identifiants

Citer

A. Abdelkefi, Dominique Guines, Lionel Leotoing, S. Thuillier. Relevant material characterization for load prediction in incremental forming. International Journal of Material Forming, 2022, 15 (3), pp.23. ⟨10.1007/s12289-022-01676-6⟩. ⟨hal-03631021⟩
68 Consultations
43 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More