Grants and Contributions

The youth will undertake marketing & sales activities to help the firm increase its visibility in the market and attract new customers.

Design and development of location-based AR (augmented reality) game

The abrasive nature of ores in mining operations causes significant wear to ground engaging tools during extractive processing which results in high maintenance costs and unscheduled process disruptions. Advances in integrating various high-performance materials to low-cost parts has faced manufacturing barriers for mining requirements due to key gaps and challenges in using laser powder direct energy deposition (DED) to volume build-up and repair complex geometries. This Project will use Artificial Intelligence (AI) to enhance DED so as to decrease process development iterations while maintaining high-accuracy deposition of fine features at fast process speeds. To feed AI analysis, existing sensors and innovative
technologies, such as laser scanners and laser ultrasonics, will be integrated as a system to monitor process parameters, part geometry and quality. A Machine Learning (ML) computational engine will be used to develop AI models/algorithms to enable quality prediction and parametric optimization through an AI-enhanced adaptive toolpath planning and evaluated on 3 relevant demonstrators (rock crusher tooth, ground engaging bucket tooth, and slurry pump impeller).

Metal additive manufacturing (AM), and more particularly the laser powder bed fusion (LPBF) process, is a very fast-growing technological field. An integral part of the Industry 4.0 concept, AM technology fully embraces the digital manufacturing vision. The development and implementation of AM on new applications are generally slowed down due to the complexity of the physical phenomena and the lack of high-fidelity reliable models. The objective of this project is to develop a reliable digital modeling platform faithfully representing the entire process to reduce the cost of development of new parts (or new materials) which currently relies on a laborious and expensive experimental approach. This project is based on the complementarity of strong expertise shared between the NRC and the academic partners and the expected results should enable industrial partners who are members of the METALTec industrial research group to increase their competitiveness in the field of AM or to accelerate the adoption of the LPBF process.

This project will support the Royal Canadian Golf Association dba Golf Canada (Golf Canada) located in the City of Oakville.

This project will support the Royal Agricultural Winter Fair Association of Canada (The Royal) located in the City of Toronto. Project activities will include support for operational expenses, implementation of COVID-19 health and safety requirements, modernization of equipment and operations and enhancing programming for the 100th Anniversary of The Royal in November 2022, helping the organization recover from the impacts of the pandemic, remain competitive among similar events in North America, and attract top competitors and visitors.

To support operational expenses, implementation of COVID-19 health and safety requirements, modernization of equipment and operations, and enhance programming for the 100th Anniversary of The Royal in November 2022, helping the organization recover from the impacts of the pandemic, remain competitive among similar events in North America, and attract top competitors and visitors.

The project aims to develop linguistic and legal tools intended improving access to justice in both official languages in Quebec. The project will reach jurists, law students, translators and the general population who may be involved in the legal system but who do not have any formal training.

The purpose of this CanExport SMEs agreement is to support small- and medium-sized enterprises (SMEs) for activities related to export market development that are part of an export business case for a specific target market, particularly where activities are targeting departmental priority markets and sectors.

The objective of this project is to improve the accuracy and the development of methods to predict the quality and quantity of crops produced on vegetable farms; this will be accomplished by analyzing the images obtained from cameras mounted on an unmanned aerial vehicle (UAV).