The objective of this project is to use optimization to improve metallic yield (the percentage of raw material that ends up as usable product) in an ArcelorMital Steel Rolling Plant. The metallic yield of the rolling operations depends upon the length of billets from which the final product is manufactured. Ideally, a single customer order would be filled using billets of precisely the length that would yield the minimum achievable amount of scrap.
A cradle is a separate structure from automotive chassis, which is used to support the powertrain and suspension system. With the application of cradle structure, the noise and vibration transmitted to passengers will be reduced and the stiffness of attachments will be increased. In other words, the riding comfort and the product reliability are improved. The research project is to design and optimize an automotive cradle considering five dominant performance requirements: local static stiffness, crashworthiness, NVH, durability and weight.
Virtual environments represented by multibody system models play an important role in many applications. Adding the possibility of the user directly interacting with such environments via physical touch using haptics can significantly enhance the usability and range of application of simulated environments.
Minimum Quantity Lubrication (MQL) is a new technology used nowadays in machining processes and is very promising for near dry machining. Compared to dry machining and flood machining processes MQL has clear economical and ecological advantages. However, MQL implementation is still applied using a trial and error approach. Limited research work has been done on evaluating the effect of MQL on product quality, especially, in aerospace materials (composites and difficult to cut materials like Inconel).
The purpose of this research project is to collect data on the actors with an interest in nanotechnology – including suppliers, users, researchers, associations and others in order to better understand the networks of innovation and to support NanoOntario’s efforts to facilitate the development of innovation networks and advance nanotechnology.
The project’s main objective is a further reduction of dependence on fossil fuels in our everyday electric appliances. Fossil Fuels are used to generate electricity and they emit dangerous greenhouse gases to the environment which one of its consequences is the familiar global warming phenomena.
This project aims to assist a company in developing Discrete Event Simulation (DES) and Human Factors modeling (HFM) capabilities. Simultaneously the project aims to explore the impact of alternative engineering designs with a Human Factors (HF) focus. These two aims will help understand factors that affect the uptake and application of the DES and HFM in work system design. The participating company is Research In Motion (RIM), which is a well known Waterloo, Ontario based telecommunication company.
This project will implement and test high speed autonomous navigation algorithms for Unmanned Ground Vehicles (UGV). The algorithms will i) sense the terrain, ii) determine the interaction between the terrain and the UGV such as forces induced on the UGV as it moves, and iii) autonomously determine the maximum allowable speed and turning radius of a UGV traversing unknown off-road terrains while maintaining safe conditions at all times for users, the UGV, and the environment.