I2.01 Computer Vision-Based MOST Analysis of Disassembly Operations
Sponsor: Center for High Performance Systems (CHiPS) Lab
Student Team: Claire Pauwels, Tyler Haug, Kenya Frias Rodriguez, Jade Ong
Faculty Advisor: Dr. Gerardo Trevino-Garza
This project applies time and motion studies, specifically MOST, to analyze wagon disassembly tasks using video-based protocols. Alongside traditional industrial engineering measurement techniques, a computer vision model is being developed to automatically detect task elements and compute MOST-based standardized times. Classical manual analysis is systematically compared with AI-driven methods, with documentation of error sources and process bottlenecks. The objective is to advance the integration of automated vision systems with established time study methodologies in practical industrial environments.
I2.02 Aumovio Robotics Dashboard
Sponsor: Joshua Duarte, Jacob Talbott
Student Team: Dylan Hahn (PM), Jimena Gonzalez, Gill Hernandez
Faculty Advisor: Dr. Gerardo Trevino-Garza
The current maintenance system is reactive and staff can only respond to problems as they happen. This dashboard will contribute to a preventative maintenance system by displaying live robotic KPIs and producing alarms when the robots function out side of their parameters. Additionally, the dashboard will contain analysis of historical robot maintenance tickets and compare it to the issues that have occurred since the implementation of the preventative system.
I2.03 Modeling & Simulation of Academic Makerspace with AnyLogic
Sponsor: Ingram Hall Makerspace (IHM)
Student Team: Natalie Huth, Aleah White, George Bruen
Faculty Advisor: Dr. Gerardo Trevino-Garza
Using AnyLogic, a multi-agent simulation of the Ingram Hall Makerspace can be constructed to account for the many variables affecting the lifespan of tools and machinery in the Makerspace. The goal of our project is to anticipate when replacement or maintenance is required in the RPM room of the Makerspace in a dynamic model that can be shaped and adapted in the future to serve Texas State University students. As such, our simulation aims to lower costs and reduce downtime for some of the most popular instruments in the Ingram Hall Makerspace.
I2.04 Humidity Control Center
Sponsor: Jared Martinez
Student Team: Marc Ojeda (PM), Cristina Marrugo, Mason Wollenzier, Leonardo Reyes
Faculty Advisor: Dr. Gerardo Trevino-Garza
AUMOVIO’s SMT screen-printing process is sensitive to environmental humidity, which directly affects solder paste adhesion and print quality. Since there is no centralized real-time system to track humidity conditions and notify engineers when levels become unacceptable, non-wetting and de-wetting defects continue to produce sensor scrap for the company. The team is tasked to create said monitoring system using the Maple Systems and EasyBuilder Pro software.