Artificial Intelligence-based optimization of Variable Blank Holder Force to reduce residual stress and improve formability; Experimental and statistical analysis
Notice bibliographique
Résumé
Abstract Many contributory factors can influence the quality of the deep drawing process, among which Blank Holder Force (BHF) plays a decisive role. Therefore, controlling the BHF during the deep drawing process can bring many advantages and act as a deterrent against process failures, including tearing, wrinkling, and fatigue due to excessive residual stress and cyclic loads. Variable Blank Holder Force (VBHF), in which the BHF varies along the punch stroke, has recently been a popular method for improving sheet metal quality in the deep drawing process. In this study, VBHF was optimized to improve the formability of the process and reduce the residual stress using two different methods of Artificial Intelligence (AI) and Response Surface Method (RSM). The main purpose of this research is to introduce a new approach based on AI for VBHF optimization and compare the result of which with that of previous methods (Statistical methods). To reach this aim, BHFs in seven different stages of punch stroke were considered as the inputs of the process, and drawn depth at the tearing moment in addition to residual stresses were considered as the outputs of this optimization process. The optimization was carried out in two forms, single and multi-objective optimization to yield the desired results. The deep drawing process was numerically simulated using Abaqus/Explicit Software, with heavy modeling calculations performed on the supercomputer, Simorgh, and the experimental studies were carried out to verify FEM simulation. Additionally, to optimize VBHF using AI methods, Artificial Neural Network (ANN) was used to define a correlation function between inputs and outputs, and a Genetic Algorithm (GA) was used to optimize the function trained by ANN. Optimization results demonstrated that although the trend of optimized VBHF using AI and RSM were considerably similar to each other, the AI results were better than that of RSM in both cases of residual stress reduction and draw ability improvement. The FEM model of deep drawing process was shown to be reliable due to its excellent agreement with experimental studies.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».