Why it matters
Without AI guidance, joints and components risk unexpected wear, NDT gaps, improper material treatment, or excessive downtime leading to AOG events, safety concerns, and costly unscheduled maintenance.
From design to safety
Design
AI-influenced overhaul strategy
Assess data streams covering overhaul intervals, part life limits, NDT findings, chrome plating quality, and exchange unit criteria to form a compliant, maintainable plan for ground time, spares, and traceable decisions.
- Main Landing Gear Assembly
- Nose Landing Gear Assembly
- Wheel and Tire Assembly
Build
Specification and acceptance checks
Define chrome plating standards, exchange unit criteria, and rivet or fastener compatibility; validate with acceptance flights, build traceability, and release to service readiness.
- Brake Assembly
- Shock Strut
- Main Landing Gear Assembly
- Nose Landing Gear Assembly
Operation
Ongoing condition monitoring
Monitor cadence, loading cycles, lubrication points, and hydraulic pressures; feed data to AI to predict wear margins, lubrication degradation, and trigger maintenance planning.
- Wheel and Tire Assembly
- Brake Assembly
- Shock Strut
Maintenance
Predicted maintenance scheduling
Translate AI outputs into service bulletins, AD compliance checks, and work orders, with exact life limits, exchange unit planning, and pre-positioned parts stocking.
- Main Landing Gear Assembly
- Nose Landing Gear Assembly
- Shock Strut
- Gear Retraction Actuator
Safety
Safety-aligned decision controls
Ensure AI recommendations pass CAMO review, Part-145 supervision, and authority sign-off for airworthiness, operational safety, and compliant maintenance execution.
- Brake Assembly
- Wheel and Tire Assembly
- Gear Retraction Actuator
Part by part
- 1
Main Landing Gear Assembly
- Watch for
- Crack growth in oleo pins; mirror threads; unexpected bushings wear over cycling and loads.
- AI action
- AI flags anomaly, estimates remaining life, triggers inspection work order and logs it into the service history.
- 2
Nose Landing Gear Assembly
- Watch for
- Hydraulic line wear at actuator fittings; corrosion on steering columns during high load maneuvers.
- AI action
- AI correlates load events with wear signals, schedules routine checks and records actions.
- 3
Wheel and Tire Assembly
- Watch for
- Tire tread depth nearing limit; wheel bore wear; brake disc scoring on specific axles.
- AI action
- AI flags impending tire replacement and brake overhaul timetable for fleet coordination with MRO.
- 4
Brake Assembly
- Watch for
- Pad wear beyond limit; caliper sticking; rotor corrosion in core braking circuits during landing.
- AI action
- AI recommends pad replacement window and potential rotor refurbishment based on life margin trends.
- 5
Shock Strut
- Watch for
- Gas seal degradation; external corrosion on strut barrel; nitrogen loss during frequent pressure cycles.
- AI action
- AI triggers STRUT leak test and reseal/overhaul scheduling within maintenance planning and spares pool.
- 6
Gear Retraction Actuator
- Watch for
- Actuator binding; hose abrasion; electrical connector wear in cold starts and vibration cycles.
- AI action
- AI issues maintenance task with inspection interval and parts list for predefined work orders.
Worked example
Catching a seal leak before a charter
Illustrative scenario with sample data.
An operator detects subtle oil residue around the landing gear during preflight; AI correlates oil leaks with seal wear indicators.
Signal in
system: landing-gear; data: oliq_v1.2; seals: main_lg_seal; readings: pressure_drop=0.8psi/hr, temp=75C; usage: 3600 cycles since last O/H.
System out
alert: landing-gear seal wear increasing; task: schedule seal kit replacement; parts: main_lg_seal, hydraulic_oil, actuator; due: 2 weeks; workorder: LG-OP-421.
Human sign-off: Part-145 certifying engineer reviews, approves the seal kit replacement and related inspection plan.
How to roll it out
Phase 1
Weeks 1 to 4: Baseline
Establish data feeds, define life limits, align with CAMO for initial AI thresholds and data integrity checks across.
Phase 2
Weeks 5 to 8: Validation
Run pilot across a subset of aircraft to refine predictions and uptime planning with exchange unit logistics and flight-hour tracking.
Phase 3
Weeks 9 to 12: Scale
Roll out full coverage, integrate with maintenance planning, CAMO dashboards, and parts provisioning networks for enterprise execution visibility.
Where people stay in charge
- Replacement intervals and life limits require CAMO approval and accountable manager authorization before maintenance.
- All airworthiness actions require Part-145 sign-off before execution and traceable records for audits ability.
- Regulatory implications must be reviewed by the authority inspector prior to maintenance program changes.
Questions owners and crews ask
What is AI used for in landing gear overhaul planning?
AI processes instrumented readings, life-limit data, and NDT results to forecast wear, determine maintenance windows, and generate auditable work orders for CAMO and Part-145 oversight.
How does AI handle NDT findings during overhauls?
AI interprets NDT results, flags anomalies, estimates remaining life, and schedules targeted inspections or component exchanges with clear documentation and traceability for airworthiness sign-off by the certified engineer in the work order.
Who signs off AI-driven maintenance recommendations?
The CAMO approves, with Part-145 certifying engineers validating execution and the accountable manager signing the release to service documentation for audit trails and regulatory compliance records.
What records are produced for audits?
AI-generated maintenance plans, life-limit calculations, exchange unit histories, NDT result logs, and release-to-service documentation that tie to airworthiness certificates and regulatory audits without gap in traceability or verification steps during routine surveys.