MétaCan
Menu
Retour à la cohorte
Enregistrement W2081401077 · doi:10.1108/01445150610658130

Flexible fixture design with applications to assembly of sheet metal automotive body parts

2006· article· en· W2081401077 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.

Notice bibliographique

RevueAssembly Automation · 2006
Typearticle
Langueen
DomaineEngineering
ThématiqueRobot Manipulation and Learning
Établissements canadiensMuscular Dystrophy CanadaUniversity of TorontoUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésFixtureAutomotive industryGRASPSheet metalEngineeringFlexibility (engineering)Set (abstract data type)Engineering drawingActuatorMechanical engineeringComputer science

Résumé

récupéré en direct d'OpenAlex

Purpose To design a reconfigureable flexible fixture for the assembly of a set of sheet metal automotive body parts. Reconfigureable fixturing permits different parts to be grasped for assembly by a fixture without the need to conduct costly redesign and fabrication of hardware fixtures, which is an industry standard in widespread use in industry. While somewhat more complex than fixtures in current use, reconfigureable fixtures provide one solution to the problem of costly redesign of fixtures due to changes in dimensions, or geometry of parts to be assembled. Design/methodology/approach We propose a novel reconfigureable fixture for robotic assembly of a number of different parts. Motivated by the marine organism, O. vulgaris , commonly referred to as an octopus, which grasps different objects or prey using suction cups, the proposed fixture has three fingers, each equipped with a suction cup, to facilitate the grasping process and increase grasp flexibility. Using this design approach, the fixture is sufficiently general in design to grasp several different parts. To position the suction cups located on the flexible fixture, two linkage‐based mechanisms are employed. Pneumatic cylinders and electric motors are used as actuators. A prototype flexible fixture has been built and experimental results with this prototype confirm the effectiveness of the proposed flexible fixture. Software has been developed to calculate the relative positions and angles in the mechanism as required for reconfiguration. Findings The proposed reconfigureable fixture, used as an end‐of‐arm tool, permits each of a set of four sheet metal parts to be successfully grasped permitting assembly of these four components, in a robotic assembly work cell. Research limitations/implications The proposed flexible fixture is a simple proof‐of‐concept device that is suitable for a laboratory setting. We do not consider part localization of parts when grasped by the reconfigureable fixture. Practical implications Assembly operations, in industrial manufacturing operations, are typically heavily reliant on hardware fixtures devices to orient and clamp parts together during assembly operations. While of great importance in such operations, hardware fixtures are very costly to design and build. Further, fixtures are designed for use with parts of specific dimensions and geometry, hence cannot be used to grasp or orient parts with even very small differences in dimensions or geometry. Typically, if parts with different dimensions or geometry are to be assembled, new hardware fixtures must be designed and manufactured to grasp and orient these parts. This lack of flexibility leads to substantial manufacturing costs associated with fixturing. Reconfigureable fixtures permit parts with different geometries to be grasped and oriented for assembly. Originality/value Reconfigureable fixtures for use in the automotive manufacturing sector is an important development due to the highly competitive nature of this industry. Rapid introduction of new models of vehicles is greatly facilitated through the use of reconfigureable fixtures which can be reprogrammed to grasp parts of different geometries required for new vehicle models.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,935
Score d'incertitude au seuil0,676

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,017
Tête enseignante GPT0,248
Écart entre enseignants0,231 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle