This project is in partnership with AUTO21. Van Rob is an automotive parts manufacturer of metal stampings with plants in the Toronto area. The objective of this internship is to evaluate the performance of a machine vision inspection system in an industrial environment. The evaluation of the intelligent neuro-fuzzy inspection algorithm used by the machine vision system known as QVision is the subject of the intern’s Master’s thesis. The original QVision was developed by a previous Master’s student. QVision has been installed on one of Van Rob’s Manufacturing cells.
The proposed research initiative consists of on-site and laboratory tests to evaluate the compaction quality of road sub-soils. To that end, we will use a self-boring pressure-meter to determine the on-site resilient modulus and compare it with results obtained by the Quebec transportation department using triaxial equipment for deviatoric loading in accordance with the LC-22-400 method. Studies demonstrate that the resilient modulus is an essential parameter for road design and analysis.
Operations research and optimization techniques are common throughout the airline industry; however, comparable tools are not yet in use for ground handling operations. This research project with Omega Optimisation, developers of Optime™ - a system for automating and optimizing critical workforce management processes, will study and propose methods for the automatic planning of aircraft-maintenance procedures.
This project is in partnership with ISIS Canada. Bombardier’s Advanced Rapid Transit (ART) solution is a medium capacity transit system, filling the gap between street‐running trams (low capacity) and heavy rail metros (high capacity). This internship aims to understand the design decisions and how new approaches and technology can reduce the costs of civil infrastructure for ART systems. The prime focus of this study is on the guideway (beams, columns, footings) and its cost.
This project will develop a mathematical model and computer tools that will minimize transportation and infrastructure costs related to the forest road network, in order to ensure the transport of wood products to receiving plants. The model will consider several decision levels, including the location of transfer yards and the choice of mode of transportation. Constraints will include the storage capacity of terminals and transportation units, and the model will take into account travel distances as well as transportation and handling costs.
This project will develop a mathematical model and computer tools that will help with the distribution of products harvested in cutblocks to plants, so as to minimize transportation expenses and the cost of moving forestry equipment. This model will consider the possibility of backhauls, which reduces empty-load transportation. Constraints will include the offer from cutblocks by period and by product, as well as the demand from plants by period and by product. The model will take into account travel distances between each starting point and each destination.
Many companies believe that the more efficient way of thinking “lean” will improve quality by eliminating waste, reducing lead time and reducing their overall costs. However, the benefits and downfalls of a lean process of manufacturing have been debated extensively. Many researchers have noted a positive improvement in productivity, quality, and efficiency which contribute positively to managers, supervisors and other white collared workers. However, some other researchers have noted negative impacts on the health of blue collared assembly workers.
Tracking and managing the dynamic location of mobile assets is critical for many organizations with mobile resources. Current tracking systems are costly and inefficient over wireless transmission systems where cost is based on the rate of data being sent. The intern is part of a team at UOttawa which focuses on tracking GPS-enabled mobile devices mounted on the asset by understanding the behaviour of typical traffic generated by a mobile device for reporting GPS data in various demographics.
Litens Automotive currently uses an axially mounted non-contact magnet based rotational position sensor in several applications to accurately and precisely measure shaft rotational position. This type of sensor has no moving parts, which allows it to be extremely durable with respect to useful life. With this robustness, coupled with low per unit cost, it has great potential to be used in mass produced items.
It is very useful to build an automatic computer system to recognize the types of vehicles passing a checkpoint given some easy-to-get data about the vehicles, such as the distances between axles, the weights on each axle. Such a system has many applications, for example, in monitoring traffic volumes and identifies the type of vehicle, which will be helpful in budgeting road maintenance costs. The main goal of this project is to develop a better methodology for cluster analysis with application to the vehicle detection problem. The simplest clustering technique is the K-means clustering.