A Condition Based Monitoring Pilot for the Baggage Handling System at the Pearson International Airport

Maintenance of baggage handling equipment, passenger boarding bridges and aircraft support equipment currently costs the Pearson International Airport (PIA) $10M annually. Much of this cost is associated with routine inspections, replacing drives, lifts and similar industrial process equipment. Current maintenance undertaken by PIA is reactive; replacing or repairing parts on the equipment after break-down. This is an expensive process. In this proposal, the intern will implement a condition based maintenance pilot on the baggage handling system (BHS) at PIA.

Development and application of Additive Manufacturing component strategies

Additive manufacturing is an innovative and promising technology that has potential to provide the aerospace industry with many benefits in the design and fabrication of aerospace components. Advantages to the additive manufacturing process include: the ability to fabricate complex designs not easily obtained through traditional manufacturing, a substantial reduction in materials waste in processing and a reduction in the total manufacturing time for multi-part assemblies.

Development of a precise and robust INS/GPS navigation system using low cost MEMS sensors dedicated to autonomous multirotor applications

ARA Robotique is a company specialized in the development of a state-of-art flight controller for light multirotor UAV. One of the critical subsystems of a flight controller is its navigation system which measures the position and the orientation of the vehicle which is then used to ensure the flight stability and to operate the UAV. To complete its flight controller design, ARA Robotique is interested in developing a robust and accurate Inertial Navigation System (INS) based on low cost Microelectromechanical system (MEMS) technology.

Centre for Operations Excellence Industry Projects 2015

The Centre for Operations Excellence Industry Projects consists of five sub-projects sponsored by four different industry partners. Each sub-project represents an important challenge for its sponsor. These sub-projects include using analytics to optimize sawmill production for Interfor; production planning for Tree Island; developing text-mining techniques to enable WorkSafeBC to predict and prevent workplace accidents; using Twitter data to enrich Boeing Canada’s maintenance and operations planning tools; and performing human resources analytics to improve Boeing Canada’s workforce planning.

Improvements for automatic pushback generation

The project aims to improve recently developed algorithms by our research team for the automatic definition of pushbacks in open pit mining that meet complex geometric constraints. Three specific objectives are pursued: a) include an approximate sequencing of blocks within a phase to enable a better discounting of the block values; b) enable to include varying geometric slope constraints according to the direction considered and c) provide, when possible, pushbacks formed of a single continuous ensemble of blocks.

Intelligent surveillance system for event detection

This project aims to develop an intelligent surveillance system for automatic event detection. The proposed system will operate in an indoor environment to notify the user of events of interest in real-time. Most standard systems use visible-light cameras and basic change detection methods (e.g. Background subtraction) to recognize simple events such as intrusion. Instead, we aim to analyze and understand complex real-life activities, which is a very challenging task due to the difficulty of analyzing a 3D scene projected on bi-dimensional images.

Designing an Autonomous Manipulator Controller for Zero-G Repair Tasks Year Two

Currently, when man-made objects in orbit around the Earth need to be disassembled or repaired, a humancontrolled robotic manipulator is used. The object in question is often not designed to be modified in this manner, and only 1 in 4 human operators at MDA (the partner organization) are able to successfully complete these notoriously challenging tasks. The goal of the proposed project is to design a computer program to learn from the successful human operators with the end result being a novel artificial intelligence that can perform these repairs autonomously, i.e.

Experimental Development and Design of Low Reynolds Number Airfoils for Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) provide a cost-effective and low-risk airborne platform for scientific and surveillance equipment. Due to the variety of instrumentation that they can carry, UAVs have enormous potential for use in a range of commercial and military sectors. However, their small size and low speed brings about aerodynamic challenges that are not present on larger aircraft. The goal of this project is to better understand these unique phenomena at a fundamental level in order to develop practical engineering solutions that will improve performance of UAVs.

Modeling and Simulation of an aircraft environmental control system (part of the Integrated Cabin Comfort Analytical Tool)

Among the different sub-systems in an aircraft, the environmental control system is the one responsible for the control of temperature, pressure and humidity in the cabin and is crucial to passenger comfort. This system has around 40 components including heat exchangers, compressors, and turbines. Recirculation at different levels complexifies the modeling and simulation of such a system. The importance of modeling this system lies in the fact that one has to verify that the cabin comfort is assured under various operating conditions.

Improving efficiency and safety in aviation industry using big data analytics (phase II)

Aviation industry uses flight data recorders (FDR) to monitor a high number of parameters during each flight it operates. It is expected that analyzing this data will provide useful information to airlines for improving flight safety and efficiency. However, this analysis is a challenging task in itself because the amount of accumulated data is enormous and also because it is diverse. To overcome these difficulties, data is first preprocessed (or cleaned) and only significant parameters are kept.

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