I1.01 Profitability-Driven Peak-Day Fleet Assignment Model
Sponsor: American Airlines
Student Team: Hyacin Rogers, Barry Williams, Brett Carter, Johnathan Cuellar, Aaron Valverde
Project Advisor(s): Chad Williams, Viswanath Potluri, Joshua Neronha
Faculty Instructor: Dr. Gerardo Trevino-Garza
This project develops an advanced decision support model for American Airlines Network Planning to maximize flight profitability on a representative peak day. By aligning fleet selection directly with financial returns, the tool identifies the highest yield flight configurations without compromising schedule feasibility. The model evaluates aircraft capability, airport restrictions, timing, and opportunity cost to optimize flight assignments between the Airbus A321neo and Boeing 737 MAX 8.
I1.02 Predictive Maintenance for Critical Facility Systems
Sponsor: Schaeffler
Student Team: Abdul Moiz , Sean Green , Milan Colmenares , Arath Guzman
Faculty Instructor: Dr. Gerardo Trevino-Garza
At Schaeffler, facility maintenance for critical air handling units is largely reactive, leaving technicians to resolve equipment failures after they occur. Our project focuses on implementing an industrial telemetry network to continuously monitor motor current, vibration, and temperature, feeding live data into the facility's building automation system. A unified web dashboard will combine real-time fault detection with historical equipment work logs, enabling proactive maintenance and eliminating unplanned facility downtime.
I1.03 Campus Network Design and Rollout Prioritization
Sponsor: CREAN Inc.
Student Team: Sebastian Martinez-Anton, Brandon Martin, Bryan Graf, Ivan Ponce, Guadalupe Ruiz
Faculty Instructor: Dr. Gerardo Trevino-Garza
CREAN, Inc., an Austin-based engineering consulting firm, is expanding its Lean Six Sigma Green Belt certification program to universities across the country and needs a repeatable way to decide which institutions to approach, and in what order. Our team is building a data-driven decision tool that uses public data program size, regional industrial employment, existing Lean Six Sigma offerings, and travel cost to rank candidate universities and determine which CREAN instructor should serve each one. The work draws on facility location modeling, multi-criteria decision analysis, and the DMAIC framework, and will be validated against CREAN's own expert judgment. At handover, CREAN will receive the tool, the dataset, and a written methodology it can rerun every year without the team.
I1.04 Manufacturing Capacity Expansion and Facility Layout Optimization
Sponsor: Yotta Energy Inc.
Student Team: Daniel Spate, Cesar Jimenez, Deniz Enser, Justyn Mckeel, Arath Guzman
Project Advisor(s): Michael Ebbinghaus
Faculty Instructor: Dr. Gerardo Trevino-Garza
This senior design project analyzes and optimizes Yotta Energy’s manufacturing system to support future production growth. The project uses discrete-event simulation, production data, and time studies to model and validate the current manufacturing process. The validated model will determine the equipment, stations, and resource requirements needed to achieve target production capacity under defined operating conditions. These results will then support the development of an optimized facility layout designed to improve production flow and accommodate future capacity needs.