About this Candidate
DAVRON CV: Candidate 1913966
MECHANICAL ENGINEER | AEROSPACE & ROBOTICS | PREDICTIVE MAINTENANCE & CAD
Core Expertise
- Aerospace propulsion reliability, predictive maintenance, and FAA-compliant engineering documentation.
- Mechanical design and CAD modeling for complex assemblies using SolidWorks, Creo, and Onshape.
- Robotics systems integration, autonomous navigation strategies, and route optimization for indoor environments.
- Simulation-driven validation with FEA, ANSYS, and MATLAB for structural and thermal performance.
- Manufacturing process optimization, CNC/robotic automation, and additive fabrication for production efficiency.
Project Background
- Developed engine health monitoring algorithms and tools deployed fleet-wide to reduce unscheduled removals.
- Led solar PV design optimizations using drone-derived 3D models, improving design accuracy and installation speed.
- Engineered autonomous robot route planning and door manipulation methods, decreasing route time by 20%.
- Optimized manufacturing processes with robotic toolpath development, cutting production time and enhancing precision.
- Designed specialized test rigs and validated aerospace components, reducing testing costs and improving durability.
Key Skills
- SolidWorks | Creo | Onshape | AutoCAD | Autodesk Suite
- ANSYS | FEA | MATLAB
- Python | C++ | Java | ROS
- 3D printing | Formlabs | Slicing software | CNC machining
- PLC | Controls | Embedded systems
- Data analysis | Excel | Statistical modeling
- Technical writing | Engineering orders | Compliance documentation
Education
- B.S., Mechanical Engineering — University of Texas at Austin
- B.S., Mathematics; Minor in Business — University of Alabama
Awards & Recognition
- GE-Reagan Scholar
- NASA Aerospace Scholar
Why Interview this Candidate?
A mechanical engineer who combines aerospace propulsion, robotics, and manufacturing experience with strong CAD and simulation skills. Delivered a CVT mitigation tool estimated to save ~$250M fleet-wide and led predictive maintenance deployments that improved engine reliability. Brings cross-disciplinary problem solving, data-driven design, and hands-on manufacturing expertise to accelerate product reliability and production efficiency.
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