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

The Royal Institution for the Advancement of Learning/McGill University

$374,550.00

Data-driven APS development for prediction of control parameters associated to in-flight particles characteristics.

FY 2024-25 · 2024-07-08

Summary
Surface engineering and thermal spray (TS) coating technologies are used to enhance base materials sustainability and to add functionality to products with applicability in a variety of industries and sectors e.g., automotive, aerospace, oil and gas, energy, and defense. Constantly changing customer needs and demands require TS coating manufacturers to be flexible enough to augment the output of TS processes in an increasingly competitive global market while delivering high-quality products at low cost. These targets can be reached by making use of existing digital technologies to capture and exploit data, leading to highly flexible and reconfigurable coating production processes, optimized equipment usage, predictive maintenance, on-line spray monitoring, and end product (i.e., coatings) quality control. Within the proposed Project it is intended to instrument a high power/enthalpy APS torch with video cameras and acoustic sensors to record continuously the process and further analyze through images and sound processing capabilities based on machine learning algorithms. These video and audio data-sets will be examined for feature selection engineering and extraction and possible trends which can indicate discernible patterns. Ultimately, if a pattern were to arise, machine learning could be leveraged to monitor and automate the spraying process.
Program
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Location
Montreal|Montréal, Quebec, Canada
Recipient Type
Academia
Business Number
119128981
Type
Grant
Source
Proactive Disclosure - Grants and Contributions

As published

Agreement End Date
2026-03-31
Agreement Number
1014103
Agreement Start Date
2024-07-08
Agreement Title
Data-driven APS development for prediction of control parameters associated to in-flight particles characteristics.
Agreement Title (French)
Développement d’un APS basé sur des données pour la prédiction des paramètres de contrôle associés aux caractéristiques des particules en vol.
Agreement Type
Grant
Agreement Value
$374,550.00
Amendment Number
0
Description
Surface engineering and thermal spray (TS) coating technologies are used to enhance base materials sustainability and to add functionality to products with applicability in a variety of industries and sectors e.g., automotive, aerospace, oil and gas, energy, and defense. Constantly changing customer needs and demands require TS coating manufacturers to be flexible enough to augment the output of TS processes in an increasingly competitive global market while delivering high-quality products at low cost. These targets can be reached by making use of existing digital technologies to capture and exploit data, leading to highly flexible and reconfigurable coating production processes, optimized equipment usage, predictive maintenance, on-line spray monitoring, and end product (i.e., coatings) quality control. Within the proposed Project it is intended to instrument a high power/enthalpy APS torch with video cameras and acoustic sensors to record continuously the process and further analyze through images and sound processing capabilities based on machine learning algorithms. These video and audio data-sets will be examined for feature selection engineering and extraction and possible trends which can indicate discernible patterns. Ultimately, if a pattern were to arise, machine learning could be leveraged to monitor and automate the spraying process.
Description (French)
Développement d’un APS basé sur des données pour la prédiction des paramètres de contrôle associés aux caractéristiques des particules en vol.
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
Ville-Marie--Le Sud-Ouest--Île-des-Soeurs
Federal Riding (French)
Ville-Marie--Le Sud-Ouest--Île-des-Soeurs
Federal Riding Number
24077
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
119128981
Recipient City
Montreal|Montréal
Recipient Country
CA
Recipient Legal Name
The Royal Institution for the Advancement of Learning/McGill University
Recipient Postal Code
H3A 2M7
Recipient Province or Territory
QC
Recipient Type
S
Reference Number
172-2024-2025-Q2-1014103