Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

13270 Completed Projects

1072
AB
2795
BC
430
MB
106
NF
348
SK
4184
ON
2671
QC
43
PE
209
NB
474
NS

Projects by Category

10%
Computer science
9%
Engineering
1%
Engineering - biomedical
4%
Engineering - chemical / biological

Human Activity-based Cycle Time Analysis for Optimizing Repeatable Processes on Manufacturing Floors

Over 70% of tasks in manufacturing are still manual and because of this over 75% of the variation in manufacturing comes from human beings. Human errors were the major driver behind the $22.1 billion in vehicle recalls in 2016. Currently when plant operators want to gain an understanding of their manual processes, they send out their highly paid industrial engineers to run time studies. These studies produce highly biased and inaccurate data that provides minimal value to the manufacturing teams. This project aims to create a smart production assistant that helps manufacturing plant operators gain unprecedented visibility into their manual production operations allowing them to optimize their worker efficiency while maximizing productivity.

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Faculty Supervisor:

Jonathan Wu

Student:

Jie Huo;Abdul Muntakim Rafi

Partner:

i-50

Discipline:

Computer science

Sector:

University:

University of Windsor

Program:

Accelerate

Electrical Material Characterization and Non-Destructive Diagnostics on Power Cable Dielectric Materials subjected to Thermal Aging – Phase II

Electric power is almost entirely transmitted through polymer insulated cables or wires in every home, factory, plant, or apparatus. If the temperature of a cable increases, it would be an indication that some accidents or malfunctions such as inflow of excess electric current occur in the cable. The generated heat, indeed, degrades the polymer insulations in cable, thus, making it unsuitable and unsafe for extra service. Therefore, it would be markedly valuable if the thermally-degraded portion in the cable can be located accurately without destroying the cable. In this project the electrical properties of cables are studied and employed as potential indicators to diagnose thermally-degraded regions of the cable. As a result, possible malfunctions in cables due to heatoverloads can be detected in an efficient, fast, low-cost, and non-destructive way which elevates the safety and lowers catastrophic risk in power transmissions.

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Faculty Supervisor:

Sheshakamal Jayaram

Student:

Amin Gorji Bandpy

Partner:

Kinectrics Inc

Discipline:

Engineering - computer / electrical

Sector:

Information and cultural industries

University:

University of Waterloo

Program:

Accelerate

Pelletization of Forest Wildfire Fuels in Western Canada

Forests in British Columbia have significant areas that need to be managed to limit the danger of fire and disease. Under current management approaches, there are few cost-effective options available to areas that are not already regularly harvested. A holistic analysis of pelletization of these materials could show that the sale of wood pellets, as well as the reduction in fire suppression and forest management costs and the increase in tax base would generate a net profit to the province and the businesses associated with the management.

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Faculty Supervisor:

Shahab Sokhansanj;Bhushan Gopaluni

Student:

Ryan Jacobson

Partner:

Empowered Startups

Discipline:

Engineering - chemical / biological

Sector:

University:

University of British Columbia

Program:

Accelerate

DESIGN OF A NOVEL HEAT EXCHANGER TEST RIG

Heat exchangers, used in building heating, ventilation and air conditioning (HVAC) systems to transfer heat from hot to cold fluids, are designed to operate under ideal conditions. However, in practice operating conditions may vary with ambient temperature or humidity. HVAC system efficiency can be improved significantly if fluid flow rates are adjusted in response to such changes. Armstrong Fluid Technology is a Canadian firm that has developed control systems to adjust the flow through building heat exchangers to maximize their efficiency. This project is being undertaken to develop a heat exchanger test rig and to use it to determine heat exchanger efficiency as a function of fluid temperatures and flow rates. The feedback control system will reduce the energy required for operating an HVAC system by approximately 30% and have a significant impact on Canada’s energy usage and greenhouse gas emissions.

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Faculty Supervisor:

Sanjeev Chandra

Student:

Chen Feng

Partner:

Armstrong Fluid Technology

Discipline:

Engineering - mechanical

Sector:

Manufacturing

University:

University of Toronto

Program:

Accelerate

Automated Target Classification for Multi-Frequency Echosounders

The oceans cover the majority of our planet’s surface but much of their depths are still a mystery. Improvements in technology have allowed for the development of instruments on underwater platforms and autonomous gliders that are able to survey the world’s oceans. One instrument, called an AZFP (acoustic zooplankton fish profiler), emits high-frequency sonar pulses and listens for backscatter (reflections) to observe fish, zooplankton, suspended sediments, and other quantities in the water column. Backscatter data are complex and time consuming to process and interpret. This study seeks to use recent improvements in Machine Learning to automate the processing and interpretation of backscatter data to reduce the time and manual effort required. Some studies using Machine Learning have already been carried out, but these focused specifically on certain species of fish and plankton and ignore everything else. However, animals in the ocean are also affected by their environment. TO BE CONT’D

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Faculty Supervisor:

Stan Dosso

Student:

Alexander Slonimer

Partner:

ASL Environmental Sciences Inc

Discipline:

Geography / Geology / Earth science

Sector:

University:

University of Victoria

Program:

Accelerate

Reliability-based finite element analysis of pipeline dents interacting with corrosion features

Corrosion, mechanical damage and cracking are the primary causes of pipeline incidents in Canada. Major incidents can significant impact the public, wildlife, and environment. Over the past ten years, the length of pipelines has increased 11 per cent, but the number of pipeline incidents has decreased 48 per cent. This is largely due to continuous improvements in pipeline safety programs across the energy industry. To make pipelines safer, the intern is dedicated to contributing to the development of the existing pipeline integrity evaluation method. The proposed project can benefit the partner organization by improving its safety evaluation method applied pipelines.

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Faculty Supervisor:

Frank Cheng

Student:

Jialin Sun

Partner:

Enbridge Employee Services Canada Inc.

Discipline:

Engineering - mechanical

Sector:

Mining and quarrying

University:

University of Calgary

Program:

Accelerate

Advancing biological phosphorus removal from wastewater using applied genomics

Wastewater can be damaging to the environment if left untreated. Microorganisms play important roles in removing harmful pollutants, such as organics and nutrients, within wastewater treatment plants. For instance, certain wastewater bioreactor designs promote the growth of specialized microbes that sequester phosphorus into their cells, which prevents harmful algal blooms in natural waters and enables sustainable nutrient recovery as fertilizer. Yet, we currently understand little about the types of microorganisms within these treatment processes, and what types of metabolisms they are performing. Such information is direly needed to develop engineering solutions that recover resources from waste and improve environmental water quality. This research will employ new genomics-based techniques to study the microorganisms that are active within a novel wastewater treatment process that AECOM is developing in partnership with the City of Penticton (British Columbia). TO BE CONT’D

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Faculty Supervisor:

Ryan Ziels

Student:

Pranav Sampara

Partner:

AECOM

Discipline:

Engineering - civil

Sector:

University:

University of British Columbia

Program:

Accelerate

Data Analysis and Consolidation for Aircraft Parts Manufacturing

Avcorp Industries provides the world’s leading aircraft manufacturers with supply chain solutions and repair support. Yield optimization, predictive maintenance, and equipment calibration are needs that are widespread throughout the manufacturing industry. The root cause of failures in product testing is often difficult to determine particularly when the failure signals are sparse relative to the available background data. Compounding the problem, the process must meet a variety of specifications for multiple customers simultaneously. This project aims to create a digital twin of the metal finishing line to leverage predictive analytics to analyze data (chemical, temperature, voltage) captured from the process line and provide new insights for an optimized manufacturing process. Leveraging the research capabilities in data analytics at Simon Fraser University, and partnership with D-Wave and SolidStateAI, Avcorp will move manufacturing fault detection processes from reactive to predictive-based. TO BE CONT’D

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Faculty Supervisor:

Fred Popowich;Steven Bergner

Student:

Padmanabhan Rajendrakumar;Jaideep Misra

Partner:

Avcorp Industries Inc

Discipline:

Computer science

Sector:

Manufacturing

University:

Simon Fraser University

Program:

Accelerate

WP 1.1.8 – Metro Reach Silicon Photonic Integrated Transceiver

Driven by cloud based applications and services, there are substantial worldwide research and commercialization efforts that are being directed toward improving the capacity of intra- and inter-data center networks. Intra-data center networks operate in the O-band (1260-1360 nm) over distances ranging from 0.5 m to 20 km, and inter-data center networks operate in the C-band (1530-1565 nm) over distances ranging from 20 km to 160 km. While these two systems share similar constraints in terms of power consumption, footprint, and cost of the employed optical transceivers, they are distinct because of the differing operating wavelengths (e.g., the dispersive properties of fibers in the C-band). Enabled by original silicon photonic circuit designs and innovative packaging, the proposed research will address key challenges in data center networks, namely increasing the capacity whilst decreasing the power consumption, size, and cost of optical transceivers deployed in these networks.

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Faculty Supervisor:

David Victor Plant

Student:

Samiul Alam

Partner:

Ciena Canada

Discipline:

Engineering - computer / electrical

Sector:

Information and cultural industries

University:

McGill University

Program:

Accelerate

Implementation of computational intelligence algorithms for the automation of business workflow at BuildMapper

KPU and BuildMapper pursued a collaborative data science project to automate and enhance BuildMapper’s core business intelligence algorithms. One algorithm will consist of a customized web crawler for the discovery and acquisition of semi-structured and unstructured construction phase information sourced from municipality websites. The other work includes the design of a SQL database for the storage of municipality download links pointing to construction phase data at the top 100 municipalities in Canada. This work will enable BuildMapper to shift from a labour intensive workflow to a highly automatized and scalable system, which will enhance and exponentially increase the velocity of data acquisition. This will enable BuildMapper to enter markets currently not feasible with the current labour intensive model.

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Faculty Supervisor:

Levente Orbán

Student:

Tina Charmchi

Partner:

BuildMapper Inc

Discipline:

Psychology

Sector:

University:

Kwantlen Polytechnic University

Program:

Accelerate

Machine Learning for Network Management and Control

The goal of this research project is to identify ways to apply machine learning technology to help communication network operators cope with the vast amounts of data they must process to understand the health of their networks and to quickly resolve problems.

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Faculty Supervisor:

Azzedine Boukerche

Student:

Abdul Jabbar Siddiqui

Partner:

Nokia Canada Inc.

Discipline:

Engineering - computer / electrical

Sector:

Manufacturing

University:

University of Ottawa

Program:

Accelerate

A mixed-methods pilot pragmatic randomized controlled trial examining the real-world effectiveness of the MOVR mobile application

There are thousands of mobile apps available for download that are geared towards health and fitness, yet limited research evaluating the real-world effectiveness of such apps exists. The MOVR app is designed specifically to enhance one’s functional abilities, fitness, and functional well-being through personalized exercise prescriptions based on individual needs. While MOVR has had anecdotal success, the app’s effectiveness at influencing physical function, fitness, and wellbeing, and its ability to enhance the quality and enjoyment of physical activity has not yet been established empirically. The objective of this research will be to examine the real-world effectiveness of MOVR for improving functional movement and perceptions of health, and to better understand individual experiences with using the MOVR app. The study will involve an 8-week pilot pragmatic randomized controlled trial (RCT) whereby participants will be randomly assigned to either 8 weeks of use of the MOVR app or 8 weeks waitlist control.

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Faculty Supervisor:

Mary Jung

Student:

Matthew Stork

Partner:

Lululemon Athletica

Discipline:

Other

Sector:

Manufacturing

University:

Program:

Accelerate

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