Innovative Projects Realized

AI-Based Fault Detection system for Mine Dewatering Systems

The removal and movement of water is an essential activity for the safe and productive operation of mines. In the mining industry pumps are often required to operate several km underground. If a pump were to fail in such a location, the results can be costly and potentially unsafe. It can be exceedingly difficult to apply conventional on-line condition monitoring systems to warn personnel of an imminent pump failure. Technosub, the industrial partner in this work, has recognized that there is presently no off-the-shelf, commercially available solution for remotely monitoring the majority of the pumps that they sell for operation in extreme locations. To address this challenge, Technosub is endeavoring to develop a small, self-contained, hardware-based fault detection device that is mounted directly to individual pumps. If a pump is about to fail, the system will then communicate this vital information to maintenance personnel. The proposed project involves the development of the computational framework for the intelligent system that will reside on the monitoring device to determine the pump’s condition. The intern on this project will gain valuable experience developing and applying advanced technologies to an industrial application.

Marketing Strategy & Content Coordinator

Envol Strategies is a people solutions firm delivering agile, cost-effective HR solutions to companies of all sizes across North America. The purpose of this role is to build a marketing strategy for our growing HR and people solutions firm. The intern will help us adapt to a post-COVID world, marketing our new mix of services and solutions to the right customers. The intern’s work will be divided into developing Envol’s marketing strategy, creating meaningful content, and driving audience engagement.

Étude sur la conciliation travail-famille et vie personnelle comme élémentde rétention des chercheurs étrangers établis au sein des territoiresrégionaux. Le cas du Bas-Saint Laurent, du Saguenay Lac St Jean et del’Abitibi Témiscamingue (UQAR, UQAC et UQAT)

Cette étude vise entre autres à mieux comprendre la gestion des dimensions temporelles (travail-famille-vie personnelle) qui conduisent à l’intégration et à la rétention des personnes immigrantes au sein des territoires régionaux du Bas-Saint Laurent/Saguenay Lac St Jean/Abitibi Témiscamingue. Elle a également pour but de favoriser des pistes d’actions desserrant le poids du travail pour favoriser la flexibilité des horaires de travail et augmenter le temps libre des chercheurs, dans une perspective d’amélioration les conditions d’intégration de rétention des chercheurs étrangers dans les universités régionales du Bas-Saint Laurent, Saguenay Lac St Jean (UQAR, UQAC et UQAT). L’objectif est de contribuer à l’avancement des connaissances sur la conciliation entre travail, vie familiale et vie professionnelle au Québec.

Sour and Sweet Corrosion Resistance of Alloys and Coatings

The oil and gas industry often contain a certain amount of CO2, H2S and chlorine compounds. H2S can cause sour corrosion and sulfide stress cracking (SSC) of stainless steels. Failures due to H2S are usually sudden with no warning. SSC is the worst type of corrosion in the presence of H2S. Many methods have been suggested to mitigate SSC and other corrosion issues in wet and sour service. Considering the design and the operation environments, the most practical solution is to change the materials of construction and select alternative material and/ coating to suit the specific need. Therefore, this proposal aims at evaluating the sour gas resistance of stainless steels and other potential corrosion-resistant alloys and coatings in sour service. This project will also increase the competitiveness of RGL in oil & gas industry by offering valuable data and experience to enhance the performance of its products for downhole applications.

Biocompatible polymers for optimisation of the production and quality of Beauveria bassiana spores

Le but de cette recherche conjointe UQÀM – Anatis Bioprotection est d’améliorer la production de

spores virulents de Beauveria Bassiana. Il fait suite au travail de formulation du projet CRSNG

Engage 2010. L’amélioration concerne la quantité et la qualité, i.e. survie, virulence et durée de vie…

AI-Based Fault Detection Development for Tele-robotically Controlled Mining Equipment

Recent years have seen many advances in the application of artificial intelligence tools in almost every industry, and the mining industry is no different. HLS Hard-Line Solutions Inc. is a leading developer and manufacturer of systems that allow mining equipment (such as trucks) to be controlled by operators, safely and comfortably from great distances, including several kilometers underground. In order to accomplish this type of control, the company must instrument the target piece of machinery with a range of sensors, cameras and control interfaces. This research aims to employ these same signals and communication systems to detect faults and mechanical problems in the mining equipment. If successful, such a fault detection system will allow maintenance personnel to be able to catch mechanical faults early, before they become serious, costly and potentially unsafe. The intern working on the project will learn how to apply valuable tools required to develop fault detection systems as well as gain a insight to the area of mining machinery and tele-operation systems. The company HLS, will gain market advantage if their products can offer the additional functionality of detecting faults in the equipment that their systems control.

Indigenous Engagement and Consultation Protocols in a Natural Resource and Mineral Rich Region: A comparison of the guidance from Indigenous Nations, Public Governments and Industry in the Golden Triangle Region

This study aims to identify the elements of Indigenous organizations’ engagement and consultation protocols, and compare with government and industry developed engagement and consultation protocols to analyze commonalities, differences and important considerations, and alignment with the United Nations Declaration on Rights of Indigenous Peoples (UNDRIP), Free, Prior and Informed Consent (FPIC) and the Truth and Reconciliation Commission (TRC) Call to Action 92. The outcomes of this project will benefit the partner’s business activities in Canada and enhance knowledge regarding Indigenous consultation and engagement, contributing to strengthen the company’s engagement strategy in the region of the study and in Canada.

Life Cycle Assessment Tool for Comparative Assessment of Sewage Sludge Technologies

Municipalities across Canada are in need of sustainable strategies to manage their sewage sludge. The goal of this project is to create an intuitive, user-friendly software tool to evaluate the environmental and economic impacts associated with alternative sewage sludge management and disposal strategies. The project will support Kerr Wood Leidal Associates, a recognized leader in stormwater and wastewater management, continue to be a progressive leader in the domain. The model will allow Kerr Wood Leidal Associates provide municipalities with insights around the effects of conventional sewage sludge management methods relative to new, innovative ones. A particular emphasis of this project will be the relative performance of sludge-based activated carbon to mitigate the life-cycle costs and environmental effects of existing management techniques.

A new design approach for mine haul road pavements with stabilized layers

Currently, the design method of haul road pavements cannot address the rolling resistance under the effects of stabilizers in pavement design. To address this, the overall objective of this research is to develop a new design approach using finite element modeling for mine haul road pavements with stabilized layers. In particular, the prediction of rolling resistance will be addressed in this new design approach. The results derived from the proposed investigation will strongly benefit the performance of truck haulage (both trucks and haul roads) in Canada’s mining sites.

Applying machine learning techniques for demand forecasting in retail

An important component to every growing retail business is demand forecasting which can affect the strategic plans of a business. The impact extends across the business’ function including budgeting, financial planning, price optimization, sales and marketing plans, capacity planning, staff management, risk assessment and mitigation plans.
In this project, we want to apply machine learning technologies to improve the accuracy and granularity of retail demand forecast. ML Models will be built from historical data and enriched with additional external factors using state-of-the-art machine learning techniques. This would result in shortening the company’s inventory age and improving the customer fulfillment rate.

A Data-Driven Approach to Formulating Best Practices for Mobile Games

The goal of the research project is to improve overall user experience in mobile games by
formulating a set of user experience best practices, or heuristics, that is specific to mobile games.
While research has been done in the past on heuristic evaluation in games, there has been little
specifically focused on mobile games. Design for mobile games presents unique challenges due to
the limited screen real estate on mobile devices and gameplay sessions of varying lengths. This
requires new, innovative solutions. My main objective at Uken Games (“UkenU) will be to improve the
overall user experience by creating a guideline of best practices for mobile game design. I will achieve
this end by conducting research into information design, interaction design and playability. I will
explore the usability of one of Uken’s mobile role-playing games (using data-driven techniques and
past company research)…

A hybrid two-way recommender system for candidate and job search

The recruitment industry faces information overload when matching qualified individuals with competitive jobs. A recommender system can effectively solve this problem by filtering relevant content in order to make recommendations, in this case matching candidates with jobs. The objective of this project is to develop such a system for two-way search and ranking of candidates given job description and vice versa; put simply this system will recommend candidates to employer and will recommend job opportunities to candidates. Existing recommender systems have their own unique benefits. This work will build upon earlier research in this field by combining the enhanced interpretability and superior performance of Knowledge Graph recommender systems with the inferencing ability of Fuzzy Logic recommender systems, ultimately developing a two-way, hybrid recommender system with increased accuracy and explainable recommendations—an innovation that will provide competitive advantage in the recruitment industry.