Increasing the stability of T-shape tube hydroforming process under stochastic framework

TitreIncreasing the stability of T-shape tube hydroforming process under stochastic framework
Type de publicationArticle de revue
AuteurBen Abdessalem, Mohamed-Anis , Pagnacco, Emmanuel , El Hami, Abdelkhalak
PaysRoyaume-Uni
EditeurSpringer Verlag
VilleLondres
TypeArticle scientifique dans une revue à comité de lecture
Année2013
LangueAnglais
DateNovembre 2013
Numéro5-8
Pagination1343–1357
Volume69
Titre de la revueThe International Journal of Advanced Manufacturing Technology
ISSN1433-3015
Mots-clésHydroforming, sensitivity analysis, Stability, Stochastic framework, Uncertainties
Résumé en anglais

Metal forming processes present several sources of uncertainties coming from material properties, geometric characteristics, and loading paths. During the manufacturing phase, such parameters may vary affecting the process stability and increasing the defect parts. Stochastic framework seems more pertinent than classical deterministic approaches to treat such problems since it is intended to include variabilities at the early design stage. In the present work, tube hydroforming process widely used in various industry applications is investigated. To ensure the process stability, loading paths should be optimized with taking into account randomness associated to the input parameters. To control the potential failure modes, the Forming Limit Stress Diagram is implemented in the finite element code to avoid necking while a simple geometrical criterion is defined for wrinkling. A global sensitivity analysis using the variance-based method is done which shows that the selected random parameters impact considerably the variance of failure indicators. Then, a numerical example of T-shape tube hydroforming process is proposed to show the efficiency of the stochastic framework. Statistical and probabilistic observations of the optimum solution show that the stochastic approach yields to an optimum less sensitive to such fluctuations which improves the process stability and minimizes considerably the percentage of defect parts in a mass production environment.

URL de la noticehttp://okina.univ-angers.fr/publications/ua16932
DOI10.1007/s00170-013-5062-2
Lien vers le document

https://link.springer.com/article/10.1007/s00170-013-5062-2