The manufacturing of safety-critical systems, such as aircraft battery packs, requires a high level of precision and consistency that is difficult to achieve with human labor alone. Factory automation presents an opportunity for manufacturers of such systems to significantly improve the quality and efficiency of their operations. This team designed and built a low-cost, portable fixture to automate the attachment of an adhesive heater blanket to a set of battery cells.

The final design uses a series of stepper motors attached to 3D-printed clamp arms. The motors are controlled by a Raspberry Pi running Python code developed by the team. Attached to the Pi is a touchscreen which displays a graphical user interface (GUI). Users of the system can load a set of battery cells into the fixture and clip a heater blanket to the clamp arms. The GUI can then start the application, which consists of the clamp arms automatically closing around the battery cells and in the process accurately adhering the blanket to the cells. The system also features an emergency stop function, allowing the user to halt the application of the blanket at any point.

Elephants walk extreme distances to forage for food in wild habitats. To simulate a more realistic environment for the elephants at the Reid Park Zoo, the team created a device that uses a programmable control system to distribute food pellets throughout the elephant habitat. The device can operate in harsh Arizona weather conditions and includes a refillable hopper to minimize zookeeper interaction with the animals. The remotely operable device aims to further the realism of the elephant habitat by encouraging more elephant exercise, requiring them to search for food rather than depending on human interaction. The most important design constraint was ensuring that the device does not cause any harm or distress to the elephants.

To allow zookeepers to easily operate the system, the unit includes a touchpad interface to program launch times, distance and angle; a remote to initiate launches from a distance; a large-capacity storage hopper; and a pneumatic pellet launching mechanism.

Enrichment items are an essential aspect of animal care within zoos. Traditionally, zookeepers remove the animals from their habitats, then manually stage the enrichment items before bringing the animals back. The team designed this device to reduce animal dependency on and interaction with zookeepers, while making animal enrichment more efficient.

They modeled the design after a standard chain-driven bucket elevator, sometimes seen in industrial and agriculture settings. The team designed a frame built with reinforced 2x4 and 4x4 lumber to emphasize structural integrity, longevity and animal safety. Equipped with a total of six buckets, the device can be pre-loaded with up to three enrichment items at a time. The team also custom designed sprockets to provide proper tension to the chain and reduce wobbling of the item-bearing buckets.

The system is driven by a 1/8 horsepower motor that uses gear ratio advantage to ensure adequate torque to move the weight of the fully loaded system. The device automatically tracks the positioning of the buckets to ensure proper delivery of enrichment items using a limit switch and Arduino controller. Zookeepers can activate the device remotely using a 433 MHz transmitter and receiver, which enables the deployment of the preloaded items individually at any time.

Flatfoot, which affects nearly 8 million individuals in the United States, occurs when the longitudinal arch in the foot collapses. Current techniques to correct flatfoot involve making large, 5-inch incisions, which may lead to longer healing times and soft tissue damage. While standard tools are used in the process, there is no standard technique or procedure.

The team developed a surgical guide system that will be placed on the outer side of the foot. Surgeons can use a custom burr remove cartilage material from the three spaces within the joint and prepare the space for flatfoot reconstruction. The guide and burr will work together to aid the surgical team in removing cartilage between the two bones. A surgeon can use the designed instrumentation to operate within a small incision (less than 1 inch) with adequate visualization of the bone. The curvature of the guide helps surgeons navigate safely through the joint when using the burr and provides a level of standardization to the surgical procedure. The system follows all medical device regulations and is crafted from ASTM F899 surgical steel.

The objective of this project is to create a fetal heart monitoring system. The system redirects magnetic field lines and uses frequency filtering to reduce noise in order to create a magnetocardiogram (MCG). The use of a novel biomagnetic sensor makes it possible to capture the fetal heart signal in a clinical environment.

The team developed a fetal heart simulator, a flux condenser, a multilayered magnetic field barrier and digital filters. The fetal heart simulator emulates relevant aspects of the electrical and magnetic activity of a fetal heart for testing purposes. The flux condenser collects and redirects magnetic fields originating from the fetal heart simulator to the sensor. The multilayered magnetic field barrier attenuates external magnetic fields. The digital filters eliminate unwanted magnetic field signals, leaving only the targeted cardiac signal. The result of this project is an MCG that displays a cardiac signal comparable to that of a fetal heart.

Flashbangs used for military or law enforcement purposes are explosive by nature and therefore potentially harmful not only to the assailant and the user, but also to the surrounding environment. Commercial electronic flashbangs attempt to replicate the size and appearance of traditional flashbangs, but may not be powerful enough to be incapacitating while remaining unharmful in the long term. The BRITE is a more versatile alternative to these flashbangs.

Powered by a rechargeable battery and equipped with high-powered LEDs and buzzers, the BRITE can be controlled remotely and run continuously for five minutes. High-powered LEDs flash at a blinding frequency and a 110 dB buzzer goes off to disorient and distract assailants. All components are housed in a cylindrical tube made of hard plastic with soft, hexagonal end caps to absorb shocks during use.

Automated systems can optimize production and daily operations in manufacturing environments. Competitive Engineering Inc. seeks to maintain quality standards by automating the process of inspecting a gear for flatness and dimensional accuracy. The team designed a system to safely complete the inspection process with repeatability and flexibility.

The system design includes a UR5 robotic arm equipped with a custom vacuum gripper, a Gocator 3D laser profile scanner and a Keyence dimensional inspection tool. The team machined fixture plates with unique rod patterns to hold gears in the correct orientation for inspection. The design focuses on the compatibility of the fixtures with the Vention workbench, vacuum gripper and the 5th Axis mounting plates. The robot is programmed to load and unload gears throughout the system while managing the results of each inspection. The system can efficiently inspect and categorize without operator interaction.

This project presents a proof-of-concept demonstration of geometric phase in an optical system, using out-of-plane mirror systems. The team built the physical mirror system with actual hardware, while they “built” the identical virtual mirror system inside of the Airy Optics VR Lab environment. The two mirror systems are linked through software so users can interact with either system to alter one or both mirror sets. The two systems can operate independently or in sync.

In the physical space, the team designed a frame that uses motors and motor drivers to enable precise rotational and linear movement of the mirrors. A custom Mathematica algorithm precisely aligns them using a generated list of 800 possible configurations. A laser with a customizable initial geometric phase propagates through the mirrors, and a polarimeter measures the polarization change. The physical system is controlled by a standalone Java application, which can communicate with the virtual system.

In the VR space, a corresponding set of mirrors displays real-time ray tracing using Polaris-M. The virtual subsystem consists of the virtual mirror setup and a graphical user interface to control each mirror position, both of which run with the Unity engine. A user can specify the polarization angle change in the optical subsystem, which alters the mirror positioning in both systems.

Tucson Electric Power aims to provide 70% of its power through renewable energy sources and reduce carbon emission levels by 80% by 2035. As the electric vehicle market increases, one part of meeting these goals is expanding the availability of affordable solar-powered electric vehicle charging stations.

This standalone system converts solar energy into electricity using a Maximum Power Point Tracking feature, a technique that optimizes the variable solar power input energy. This optimal energy is then extracted and routed to the charging circuit subsystem that contains a 240kV step up isolation transformer and a buck converter that steps down the voltage to power an Arduino MEGA 2560 microcontroller. The Arduino monitors and communicates digital control to the closed-loop cooling subsystem to keep the internal temperature within operable limits.

The solar charging circuit, microcontroller and cooling system are enclosed in a National Electric Manufacturers Association 3R-rated external housing system, making the off-grid solar power converter able to withstand extreme weather conditions. This system will allow users to charge electric vehicles directly from solar panels without grid interconnectivity.

Vegetation stress is a key indicator of crop health, which often is determined using manual field analysis. This project presents a real-time drone analysis as a cost- and time-saving alternative. The Crop Level of Stress Analysis with Visual Export (CLOSAVE) software system can detect and categorize the level of stress in vegetation leaves.

The design is split up into two elements. The primary element is the CLOSAVE software, which receives video from a drone as it flies over a crop and then uses machine learning algorithms to indicate areas of stress detected on the plant. A commercial off-the-shelf color camera captures the video, and the software is pre-trained to recognize vegetation stress indicators. The second element is a drone, custom-built entirely by the team, that uses parts tailored to the design requirements of the software.