Ryan Wells

Highly motivated soon-to-be graduate with a strong background in Industrial Engineering and practical experience gained through academic projects and leadership positions. Demonstrates excellent teamwork, problem-solving, and time-management skills. Ready to launch a career and deliver significant contributions to an organization with commitment and drive.

• Interdisciplinary Capstone
• Lean Engineering
• Production Systems Analysis
• Simulation Modeling & Analysis
• Quality Engineering
• Engineering Experiment Design
• Software for Engineers
• Systems Cybersecurity
• Design for Additive Manufacturing
• Embedded Computer Systems
• Human Factors & Ergonomics
• Operations Research

Automated Parcel Identification Tracker (Amazon Project)

• Developed project proposals, system requirements, verification methods, and conceptual designs to meet functional requirements and project goals
• Delivered technical data packages that included engineering changes, technical drawings, user manuals, and troubleshooting guides, Presented Preliminary Design Review (PDR) and Critical Design Review (CDR) to mentor and sponsor, incorporating feedback to improve the system architecture
• Organized a multi-disciplinary team to identify root cause and develop a corrective action, which resulted in 100% identification accuracy of non-conforming material
• Created a simulated test environment using an off-the-shelf conveyor system and modified its operational parameters, both mechanical and electrical, to more closely emulate real world operational environment, Provided technical support to Amazon engineering to facilitate system integration in Amazon fulfillment center

Theme Park Attraction Data Analysis Tool

• Developed a data driven analysis tool to optimize wait times at Walt Disney World, processing 10,000+ data points for operational process improvements
• Designed and implemented a VBA-based user interface, improving report generation speed by 40%

QuikTrip Store Checkout Simulation

• Designed and simulated a checkout system to model customer flow for 500+ transactions per day, improving cycle time by 15%
• Applied continuous improvement principles by conducting an efficiency analysis comparing self-checkout and human checkout systems, increasing overall throughput by 25%

Lean Manufacturing (Gore Certified))