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Grant: Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives

The University of Western Ontario

$239,800.00

AI-Powered Self-Optimized and Self-Controlled Laser Polishing of Tooling and Extruded Aluminum Surfaces.

EF 2021-22 · 2021-04-12

Résumé
A goal of the next industrial revolution consists in integrating digitalization, artificial intelligence (AI), and automated decisions into all phases of advanced manufacturing from product design to end applications. This integrated approach will be used to advance laser polishing (LP) technology towards self-optimization and self-control for process stability, adaptability, and quality. During the Project, several AI-based methods will be developed and applied to create a LP technology application that can replace the manual and experience-based process parameter selection to finish a piece. The LP technology application, with its augmented AI-optimized and AI-controlled capabilities, is intended to interconnect three critical components (design, fabrication, quality) in order to reduce the cost, increase process efficiency, and open new opportunities associated with LP of tooling and extruded aluminum surfaces.
Programme
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Emplacement
London|London, Ontario, Canada
Type de bénéficiaire
Academia
Numéro d'entreprise
108162587
Type
Grant
Source
Proactive Disclosure - Grants and Contributions

Tel que publié

Agreement End Date
2024-03-31
Agreement Number
972125
Agreement Start Date
2021-04-12
Agreement Title
AI-Powered Self-Optimized and Self-Controlled Laser Polishing of Tooling and Extruded Aluminum Surfaces.
Agreement Title (French)
Système autonome à optimisation automatique par intelligence artificielle de polissage laser des surfaces d’outillage et des surfaces d’aluminium extrudé.
Agreement Type
Grant
Agreement Value
$239,800.00
Amendment Number
0
Description
A goal of the next industrial revolution consists in integrating digitalization, artificial intelligence (AI), and automated decisions into all phases of advanced manufacturing from product design to end applications. This integrated approach will be used to advance laser polishing (LP) technology towards self-optimization and self-control for process stability, adaptability, and quality. During the Project, several AI-based methods will be developed and applied to create a LP technology application that can replace the manual and experience-based process parameter selection to finish a piece. The LP technology application, with its augmented AI-optimized and AI-controlled capabilities, is intended to interconnect three critical components (design, fabrication, quality) in order to reduce the cost, increase process efficiency, and open new opportunities associated with LP of tooling and extruded aluminum surfaces.
Description (French)
L’intégration de la numérisation, de l’intelligence artificielle (IA) et de l’automatisation des décisions dans toutes les phases des technologies de fabrication — de la conception jusqu’aux applications — compte parmi les objectifs de la prochaine révolution industrielle. Cette approche intégrée sera utilisée pour perfectionner la technologie du polissage par l’autonomisation et l’optimisation automatique pour en accroître la stabilité, l’adaptabilité et la qualité. Plusieurs méthodes fondées sur l’IA seront créées et utilisées pour créer une technologie de polissage laser capable de remplacer la sélection manuelle et expérimentale des paramètres du processus pour la finition d’une pièce. Cette technologie de polissage laser optimisée et contrôlée par l’IA vise à intégrer trois composantes critiques (conception, fabrication et qualité) afin de réduire le coût, d’accroître l’efficacité du processus et de créer de nouvelles possibilités dans le polissage laser des surfaces d’outillage et des surfaces d’aluminium extrudé.
Expected Results
In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.
Expected Results (French)
À court terme, les résultats prévus seront des collaborations renforcées entre l'industrie, le milieu universitaire et le gouvernement pour soutenir l'excellence en recherche. À moyen terme, les résultats attendus seront le développement de nouvelles technologies potentiellement perturbatrices avec des collaborateurs. À long terme, trouver des solutions collaboratives aux défis des politiques publiques et créer des systèmes d'innovation plus solides.
Federal Riding
London North Centre
Federal Riding (French)
London-Centre-Nord
Federal Riding Number
35052
NAICS Code
541710 - R&D in the physical, engineering and life sciences
Organization Code
nrc-cnrc
Organization
National Research Council Canada | Conseil national de recherches Canada
Program Name
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Name (French)
Programme de collaboration en science, en technologie et en innovation - Initiatives de collaboration en R-D
Program Purpose
Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.
Program Purpose (French)
Collaborer à des programmes multipartites de recherche-développement dans le but de profiter de la synergie entre la recherche transformatrice à haut risque et à haut rendement et le potentiel de découvertes scientifiques et de percées technologiques révolutionnaires dans des secteurs d’intervention prioritaires.
Recipient Business Number
108162587
Recipient City
London|London
Recipient Country
CA
Recipient Legal Name
The University of Western Ontario
Recipient Postal Code
N6A 3K7
Recipient Province or Territory
ON
Recipient Type
S
Reference Number
172-2021-2022-Q1-972125