The Challenge
Scheduling at 30,000 Feet
Running an aviation university is exponentially harder than running a standard college. You aren't just booking classrooms; you are booking aircraft. The Complexity: The university struggled with a "Four-Dimensional" scheduling problem. A flight lesson requires the simultaneous availability of: 1) A Student, 2) A Certified Instructor, 3) An Airworthy Aircraft, and 4) A Valid Weather Window. Doing this manually on whiteboards resulted in grounded planes, wasted instructor hours, and students falling behind on their flight hours.
The Solution
Algorithmic Flight Operations
We built a specialized Aviation ERP that serves as the brain of the campus. It integrates academic grading with flight operations, creating a seamless flow from the classroom to the cockpit.
Key Architectural Pillars:
01. The "Auto-Roster" Algorithm
We engineered a constraint-based scheduling engine. It automatically matches students with instructors and available aircraft (Cessna/Piper) while adhering to strict Civil Aviation Authority (CAA) rest-period regulations.
02. Fleet Maintenance Tracker
Safety first. The system tracks the "Hobbs Meter" (engine hours) of every aircraft. When a plane nears its 50-hour or 100-hour inspection interval, the system automatically blocks it from the schedule and alerts the engineering team.
03. Digital Pilot Logbooks
No more paper logs. Students input their flight data via a mobile tablet immediately after landing. The system validates the hours against the aircraft's GPS data and syncs it to their academic transcript.
04. Simulator Asset Management
Simulators are expensive assets that run 24/7. We built a booking system that maximizes utilization, allowing students to book practice slots at 3 AM if needed, accessed via RFID student ID cards.
The Results
Operational Altitude
Metrics:
- 25% Increase in fleet utilization efficiency
- Zero Regulatory violations regarding instructor rest periods
- Real-Time Tracking of student progression toward Private Pilot License (PPL)
- Paperless Operations for flight briefing and debriefing notes
The Tech Stack
Precision Engineering
Backend:
Python (Django) - Chosen for its ability to handle complex mathematical scheduling logic
Frontend:
React.js - For a high-speed, responsive dashboard used by dispatchers
Database:
PostgreSQL - For robust data integrity of flight records
Integration:
ADS-B API - To track real-time aircraft positions