Rules and methods for exploring and utilizing additive manufacturing-enabled part consolidation potentials in product redesign
Notice bibliographique
Résumé
Part consolidation (PC) is an effective design technique to reduce part count and simplify product architecture. Through PC, it brings numerous benefits such as reduced assembly operation, decreased supply chain management cost, and increased structural reliability. Consolidation of parts, however, may lead to increased manufacturing difficulty in terms of complex geometry and material composition. Constrained by the capability of conventional manufacturing methods (e.g. machining and casting), PC is only applicable to components having simple geometries, no relative motion, no material variance, and no blockage of assembly access of others. As additive manufacturing (AM) evolves into an end-of-use product fabricating method, such constraints of PC have been largely relaxed, and PC has become one of the primary motivations of using AM. However, the rules and methods for exploring such emerging PC potentials are obsolete, and the understanding of how to utilize these PC potentials in a general product redesign process is very limited. To fill these gaps, three contributions are made in this thesis. First, a methodological framework enabling full exploitation of AM-enabled PC potentials in product redesign is proposed. The framework is highlighted by three design flows: core flow, complementary flow, and innovative flow. The core flow is dedicated to screening, consolidating, and refining parts that are highly feasible for consolidation. The complementary flow is supplementary to the core flow to further investigate the slight consolidation potential for parts that are rejected by the core flow. The innovative flow works in parallel with the prior flows. It aims at enlarging the design solution space by advocating design for function throughout the synthesis process of working principle, product layout, design space, material, and architecture. Amongst the three proposed flows, the core flow is the primary focus of this research and has been thoroughly investigated and implemented. Second, new candidacy rules, principles, strategies, and tools to support the systematic and automatic identification of PC candidates are developed. Third, a functional entity-based design method is proposed to aid the transition from the candidacy assembly design to the functionally-equivalent consolidated design. In the end, a computer-aided design tool is developed to implement the proposed core flow, which paves the way for better exploring and utilizing AM-enabled PC potentials in the redesign process of a complex product.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 ».