Grants and Contributions:
Title:
Data-driven APS development for prediction of control parameters associated to in-flight particles characteristics.
Agreement Number:
1014103
Agreement Value:
$374,550.00
Agreement Date:
Jul 8, 2024 - Mar 31, 2026
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.
Organization:
National Research Council Canada
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.
Location:
Montreal, Quebec, CA H3A 2M7
Reference Number:
172-2024-2025-Q2-1014103
Agreement Type:
Grant
Report Type:
Grants and Contributions
Recipient Business Number:
119128981
Recipient Type:
Academia
Recipient's Legal Name:
The Royal Institution for the Advancement of Learning/McGill University
Federal Riding Name:
Ville-Marie--Le Sud-Ouest--Île-des-Soeurs
Federal Riding Number:
24077
Program:
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
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.
NAICS Code:
541710 - R&D in the physical, engineering and life sciences