Radius Putty Machine Tool Redesign
Notice bibliographique
Résumé
This report presents the approach taken to design a solution to a Radius Putty Application System under the University of Manitoba Innovative Design for Engineering Applications (UMIDEA) Program for Carfair Composites Inc. (Carfair). The system was created by Magnum Venus Products (MVP) by modifying an existing resin spray gun. The system was redesigned to be used to fill putty in areas of sharp radii. However, the system proved to not meet all of their needs sufficiently, thus, it had been retired. Upon investigation, there were several issues with the putty gun. The primary issues were an inconsistent catalyst concentration in the putty as well as over-spray occurring, where putty was sprayed into areas beyond where it was intended. After investigating, the team developed a list of concepts as to how to rectify the issues by utilizing various concept generation techniques. From there, six primary concepts were put into a Weighted Decision Matrix. This provided the top three ranked solutions, per Carfair’s request. The UMIDEA team chose to begin by investigating the feasibility of the top-ranked solution for catalyst concentration inconsistency issue. The solution was to remove the putty supply pump and obtain a putty with a lower viscosity. The putty supply pump had been added to the putty system by Carfair. They assumed this pump was required due to the higher viscosity putty. However, when the team tested the system, it was demonstrated that the main pump was able to pump sufficiently. This led the team to believe that perhaps a second issue with the system was material storage. Upon inspecting the previous putty storage practices, it was observed that the containers would sit open to the air for extended periods of time. This caused the putty to begin to harden, and it a possible cause for why the main pump had previously been unable to pump the putty. The investigation also demonstrated that in varying the pressure of the system and/or the catalyst ratio, the consistency in the catalyst concentration varied greatly. Unfortunately, there were putty supplier issues, and Carfair was only able to obtain the putty very late into the project timeline. The testing did not provide a sufficient result, and there were multiple possible sources of error. Due to time constraints, the testing of the final design was far more brief than the UMIDEA team had planned. The testing found that the optimum settings were 35 psi pressure with a 2.5 percent catalyst concentration. However, the team prepared a list of further testing that should be performed in order to further investigate these settings, as the result was not within the Client’s specifications.Two different components were also designed. To eliminate the over-spray issue, the air hose connections in the putty gun were removed. A new conical nozzle tip was designed in order to increase the ease of extruding the bead into the sharp radii. A foot for the putty infeed transfer rod was designed to be used in place of where the supply pump had previously connected. The transfer rod would often sit flat on the base of the putty bucket, and would suction to the bottom, resulting in poor putty flow. The foot was designed with the intent of adding gaps beneath the rod. The team also made new work instructions on how to properly use the retired putty application system. A list of recommendations for future investigation was also prepared. The team was able to achieve a 69 percent reduction in the project cost from the approved budget and predicts that by following the list of future recommendations, all other project needs and specifications would be met.
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.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,004 |
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 source (Gemma direct ou Codex distillé), 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 ».