MTA Scenario Files - Summary
Documentation for Maintenance Task Analysis Teaching Scenarios
Overview
This tool contains realistic aerospace maintenance scenarios designed for teaching Maintenance Task Analysis principles. Each scenario demonstrates different aspects of maintenance planning, delay modeling, and resource constraints.
Scenario 1: Aircraft Main Landing Gear Tire Replacement
ATA 32 - Landing Gear 9 SubtasksDescription: Complete tire replacement procedure on Boeing 737 main landing gear
Key Risks:
- Tire availability (25% delay probability)
- Wheel balancer availability (20% delay probability)
- Inspector availability (20% delay probability)
Learning Focus:
- COTS (Commercial Off-The-Shelf) parts procurement delays
- Shared equipment constraints (wheel balancer)
- Personnel skill requirements and certification bottlenecks
Scenario 2: Aircraft Engine Oil Change
ATA 79 - Oil System 9 SubtasksDescription: Routine engine oil and filter change on turbofan engine
Key Risks:
- Oil filter availability (15% delay probability)
- Engine oil stores availability (20% delay probability)
- Oil drain equipment delays (10% delay probability)
Learning Focus:
- Consumable parts management (oil, filters)
- Hazardous material handling procedures and time impacts
- Engine run-up verification and potential delays
Scenario 3: Avionics System Operational Check
ATA 34 - Navigation 9 SubtasksDescription: Post-maintenance functional check of avionics and navigation systems
Key Risks:
- Test equipment availability (25% delay probability at connection phase)
- Specialized test equipment delays (10-15% across multiple steps)
- Technician certification requirements and scheduling conflicts
Learning Focus:
- Special equipment dependencies and availability constraints
- Test equipment calibration and certification requirements
- Electronic system testing procedures and verification time
Using These Scenarios for Teaching
Recommended Teaching Flow (4-hour session):
- Hour 1-2: Students review detailed MTA documentation using the Aircraft Tire example. Understand MTTR, delay types, and resource constraints.
- Hour 3: Run simulations on all three scenarios using the MTA Simulator. Compare baseline results and identify patterns.
- Hour 4: Analyze variance drivers in each scenario. Discuss which factors contribute most to schedule risk.
Comparison Exercise for Students:
After running simulations, students should analyze and compare:
- Which scenario has the highest variability (coefficient of variation)?
- Which delay type (DELAY1/DELAY2/DELAY3) dominates in each scenario?
- Which specific tasks would benefit most from additional resources or inventory?
- How does the probability of on-time completion change with different target times?
Data Structure
All scenario files use the same standardized format:
| Column | Description | Format |
|---|---|---|
| SUBTASK | Descriptive name of the maintenance step | Text |
| MTTR | Mean Time to Repair (minutes) - baseline duration | Numeric (float) |
| DELAY1 | Personnel delay probability | 0.00 to 1.00 |
| DELAY2 | COTS/Parts delay probability (only applies when COTS=1) | 0.00 to 1.00 |
| DELAY3 | Special equipment delay probability (only applies when SPECIAL=1) | 0.00 to 1.00 |
| COTS | Binary flag indicating if subtask requires COTS parts | 0 or 1 |
| SPECIAL | Binary flag indicating if subtask requires special equipment | 0 or 1 |
Important Notes:
- DELAY2 only applies when COTS=1
- DELAY3 only applies when SPECIAL=1
- Base subtask durations follow a normal distribution with mean=MTTR and std=0.1*MTTR
Delay Impact Values
When delays occur in the simulation, the following time penalties are applied:
For more information or to run simulations, return to the MTA Simulator