Cavendish Agri Services, a major fertilizer manufacturer in Atlantic Canada, is searching for a solution to capture dust particles that impact the quality of their final fertilizer product. Specifically, the O’Leary fertilizer facility is experiencing a reduction in high-quality products and loss of product due to caking (the adherence of fertilizer prills and dust when liquid fertilizer is introduced during the mixing process).

Cavendish Agri Services fertilizer mixtures are composed of various raw bulk materials that, through shipping and the natural form of the material, can produce a significant amount of dust. Dust increases the clumping and caking of the material to itself and to the equipment used to mix it when raw materials are combined with liquid additives. The team has proposed an angular rotary sifter to remove most of the dust before it reaches the liquid additive stage in the blending process. During this stage of dust removal, the team intends to reduce the fertilizer clumping effect. Collecting dust permits later repurposing and helps ensure Cavendish maintains the highest level of quality and sustainability that their customers expect.

Island Abbey Nutritionals (IAN) is a PEI food science company seeking to innovate their processes and increase production rates. The curing stage, where hot air is circulated across gummies to dry and cure them, currently creates a bottleneck because of slow curing. Bulk gummy curing in the existing 13 large chambers at IAN requires 36-48 hours per batch. The risk of testing a potential improvement in these chambers is too high, given the value of the product. Therefore, this project’s objective is to design and create a benchtop testing chamber (BTC) that thermodynamically scales the full chambers

A test chamber enables IAN to conduct internal exploration and analysis to vary settings (temperature, humidity, airflow) and optimize curing conditions, reducing product risk. The design emphasizes modifiability, and the team is providing a Standard Operating Procedure (SOP) with operation, maintenance, and testing recommendations to support the operators. Relevant fields include research and development, control systems, food science, and industrial design, with significant elements of mechanical and electrical engineering.

Wind Turbine blades’ material composition includes up to 70% of fiberglass. During end of life processes, blades are partly burned and the remaining inert fiberglass is sent to landfill. This solution is unsustainable as it is harmful to the environment. Proposed solution would include processing of turbine blades to obtain strands of fiberglass that can be utilized as an aggregate to concrete to maximize its strength. Upon testing and analysis, it was identified that 1.5% volume fraction is the optimum quantity of fiberglass that can result in 30% increased overall concrete strength.

The PEI Department of Housing and Communities (DHC) works closely with the Department of Transportation, Infrastructure and Energy (DTIE) to approve approximately 1200 entranceway permits annually. These permits ensure that new driveways meet the minimum safe sight distance (SSD) requirement as outlined in the PEI Highway Access Regulations. SSD is defined as the stopping distance required for a driver with a 1.05 m eye level to see an object 0.4 m or higher on the road and is critical to ensure oncoming traffic has sufficient time to stop for a car exiting the driveway. 

The DHC and DTIE currently rely on manual processes to measure SSDs for new entranceway applications. This process is both time-consuming and dangerous for workers on the road. They have requested a system to measure and report safe-sight distances for road access points, such as new driveways. 

Over the course of the semester, the team has developed a software package to measure SSD remotely from a computer by leveraging elevation models from PEI’s 2020 LiDAR dataset. The solution features a user-friendly interface that runs ArcGIS Pro from the back end to measure the line of sight from a specified driveway location and the SSD achieved. The two main assessment modes are a single-point mode for testing an individual driveway or a multi-point mode for testing longer sections of road for the safest driveway placement. Once an assessment is complete, a Survey123 template is automatically populated with report details and is exported to PDF format.

The Ulverton Wool Mill (known locally as the Moulin a Laine d’Ulverton) is a heritage site in Ulverton, Quebec, that features a textile mill built in 1849. The Moulin features a machine known as a spinning mule, estimated to be built between 1870 and 1900. These machines are used to spin wool into yarn in much larger quantities than was possible before its invention. The machine was built by Davis and Furber, a machinery company that went out of business in 1982, so very little documentation exists about this machine. The team was tasked with recreating that documentation that has been lost to time. 

This is a reverse-engineering project, where instead of designing a solution to a problem, the team instead tries to figure out how the solution was designed. The goal is to produce documentation for the mule that will assist the Moulin in the maintenance and preservation of the machine, and engaging the Ulverton community in the restoration of old textile machinery. 

The team has created a Comprehensive Multimedia Collection that takes the form of a website, so all of the documentation can be put into one easily accessible place. The Collection was designed to be scalable to bring the Ulverton community together and allow for easy collaboration between other textile mills. That way, the Collection is useful to the Moulin long after the team’s involvement in the project. 

Of course, the team also created some documentation to make sure the Collection is off to a strong start. The team was able to create CAD drawings of a section of the mule to better understand how the machine works. This machine is entirely mechanical, so the parts all have to work together very precisely in order for the machine to run. This was captured in the motion study the team created, and the assembly of the machine was simulated with the exploded-view drawing. All of these are annotated in a separate file, and added to the Multimedia Collection. 

The Ulverton Wool Mill team will be present at UPEI’s annual engineering expo, on April 24th from 1-5pm. The team will have an interactive station featuring the website, some simulation videos, and some photos of the beautiful Ulverton scenery. UPEI welcomes you to the engineering expo, and the Ulverton Wool Mill team hopes you will pay them a visit!

The Teams Clinic Partner, UPEI Facilities, manages and maintains campus buildings, performing general maintenance, repairs, and upgrades, and overseeing various other activities to ensure a clean and safe campus for all staff and students. Our third-year design team consists of four members: Luke Jennings, Joshua Hall, Peter Benedict Arackal, and Elijah Dodd. UPEI Facilities has requested that the team conduct an energy audit of the campus to identify areas for improvement and retrofits to reduce overall energy use and save money. The team has been working on this project over the last two semesters, targeting three main buildings, and has used energy auditing and modelling software to achieve these goals.

 Our team targeted three buildings on campus: Memorial Hall, the National Research Council of Canada, and the Atlantic Veterinary College. Memorial Hall is one of the oldest buildings on campus and has not undergone any major upgrades since it was built, leaving many inefficient areas that could be improved, such as replacing its old windows and weatherstripping, and upgrading its lighting to more efficient LED bulbs. The team not only investigated older, inefficient buildings but also targeted buildings that consume a high amount of energy, such as the NRC and AVC. The NRC is primarily used for research and is home to many lab spaces and intensive equipment, such as fume hoods. One of the novel approaches the team took for NRC was to assess the implementation of fume hood occupancy controls, which monitor occupancy and adjust air extraction levels to minimize use during low occupancy, rather than leaving them fixed and pulling air constantly, which consumes significant energy. Two other retrofits tested were upgrading the original 2009 chiller used to cool the building to a more energy-efficient model, saving a large amount of electricity. Another easy change, like that done with Memorial Hall, was to upgrade all lighting to LED. The AVC is similar to NRC, with many lab spaces and equipment, drawing significant power. Similarly, lighting upgrades were tested, and the same approach using fume hood occupancy controls was assessed, as they use the same static system. The final retrofit assessed was upgrading various equipment, such as their freezers and incubators, to newer models. Much of this equipment is from the early 2000’s, and more efficient models are available.

 To test and assess these retrofits, RETScreen, an energy modelling software, was used. The software allows for precise modelling of a building, inputting parameters for windows, walls, and doors, and enabling changes to be made in a proposed case. Additionally, installation costs should be considered, as one project requirement was to implement solutions with a return on investment within 20 years. RETScreen was successfully used to model all these buildings, apply and test various retrofits to determine their viability, and create reports and recommendations that can be presented to the clinic partner to help assess and determine the viability of future retrofits around campus. Implementing the mentioned retrofits across the three targeted buildings allowed the team to reduce each building's energy use by 10% and, therefore, save on monthly energy costs.

Whisperwood Villa is a long-term care facility that does their 100 residents’ laundry on-site. Currently, residents’ families must label clothing before facility move-in, but they are not consistently labelling clothing. Unlabelled clothing cannot be sorted by laundry staff or returned to residents, resulting in $14,000 of textile waste annually from lost clothing. The objective of this project is to reduce the volume of lost clothing in the facility through labelling and sorting process improvements to reduce textile waste and staff frustration. 

The two main problems are the labeling inconsistencies and the bundling of small items. Resident families are currently required to have all their clothing labeled before entering the facility, however, due to many reasons, the labeling is not always done or done correctly. If a label is not applied correctly, it falls off in the wash and the clothing item can no longer be returned. The second problem is that smaller items such as socks or undergarments are bundled together with rubber bands and labeled with cardboard before being sent out for delivery. The labels are often lost and the bundles can fall apart. 

The solution that the team came up with is split into two parts. To solve the labeling issue, the team suggests Whisperwood Villa purchase a thermoset labeling system. This includes a heat press, label printer, and labels. The solution allows laundry staff to label incoming clothing which eliminates the responsibility of labeling from the families and the frustration that came with it. To solve the bundling problem, the small items will be bundled into a mesh bag with permanent labels and a zipper. These bags will help keep the bundles together and never lose their label. Upon implementing both solutions, Whisperwood Villa will see a significant decrease in lost clothing and frustration within their facility.

Whisperwood Villa is a long-term residential care home in Prince Edward Island, Canada, that provides 24-hour nursing and community care supervision to its residents, including medication management and care planning. The project addresses the limitations of the facility's meal labelling system, which relies on printed paper labels attached by tape to food trolleys. This current process is prone to errors, wear, and unsanitary conditions. The team designed a wireless electronic meal labelling system comprising a colour e-paper display and an LCD module, housed in a 3D-printed PETG mount and driven by an ESP32 microcontroller. Each display unit shows resident-specific dietary information — including name, room number, diet type, texture, allergies, and fluid recommendations — and updates automatically via a Raspberry Pi 4 gateway over a local Wi-Fi network.