Bogor–
AI Boosts Fighter Aircraft Maintenance to Strengthen Indonesian Air Force
Readiness. A recent study by Janjang Satya E.W., Budi Santoso, and Yulianto
Hadi from The Republic of Defense University was published in the Contemporary
Journal of Applied Sciences (CJAS), Vol. 4 No. 2 (February 2026).
A
recent study by Janjang Satya E.W., Budi Santoso, and Yulianto Hadi from The
Republic of Defense University highlights how AI-driven maintenance management
can significantly improve aircraft reliability, availability, and operational
readiness.
Why
Fighter Aircraft Maintenance Matters
Fighter
aircraft are among the most complex and costly defense assets. Their
operational readiness directly determines the Air Force’s ability to protect
national airspace and execute strategic missions.
The
study emphasizes that traditional, paper-based maintenance systems are often
time-consuming, prone to human error, and less responsive to real-time
operational demands. As aircraft systems become increasingly sophisticated,
maintenance management must evolve accordingly.
Drawing
on Terry Wireman’s maintenance management theory, the researchers focus on
three key performance indicators:
- Availability – percentage of time aircraft
are ready for use
- Reliability – ability to operate without
failure
- Maintainability – speed and ease of repair
AI,
the authors argue, can strengthen all three indicators.
Real
Data from Iswahjudi Air Force Base
The
study analyzes fighter aircraft maintenance data from Iswahjudi Air Force Base
between 2020 and 2023 (Table 1, page 142).
Two
main aircraft types were observed:
- F-16
(Skadron Udara 3)
- T-50i
(Skadron Udara 15)
Maintenance
activities were categorized into:
- Light
maintenance
- Medium
maintenance
- Heavy
maintenance
- Unscheduled
maintenance
Key
Trends Identified
According
to Table 1 (page 142):
- F-16
light maintenance consistently exceeded planned targets in 2020–2021.
- Unscheduled
maintenance for F-16 decreased significantly by 2022–2023.
- T-50i
experienced fluctuating unscheduled maintenance, peaking in 2022 before
declining in 2023.
The
decline in unscheduled maintenance for F-16 suggests improved scheduled
maintenance effectiveness. However, fluctuations indicate the need for more
predictive systems.
The
readiness chart on page 144 further illustrates variations in
operational availability between the two aircraft types from 2020–2023.
These
findings show that maintenance remains reactive in several cases—an area where
AI can make a transformative difference.
How
AI Enhances Fighter Aircraft Maintenance
The
researchers outline several practical AI applications:
1️⃣ Predictive Maintenance
Fighter
aircraft generate massive sensor data covering engine performance, avionics
systems, and structural conditions.
AI
can:
- Detect
anomalies early
- Predict
component failure
- Recommend
proactive maintenance
- Reduce
unexpected downtime
This
improves Mean Time Between Failures (MTBF) and reduces Mean Time to Repair
(MTTR).
2️⃣ Optimized Spare Parts Management
AI
analyzes historical and operational data to forecast spare parts demand. This
ensures:
- Parts
availability when needed
- Reduced
overstocking
- Lower
operational costs
Given
the high cost of fighter aircraft components, efficient inventory management is
critical.
3️⃣ Real-Time Monitoring and Supervision
AI
supports management functions described in classical management theory:
- Planning – Data-driven maintenance
forecasting
- Organizing – Coordinating maintenance units
- Actuating – Executing maintenance based on
predictive alerts
- Controlling – Monitoring performance and
detecting deviations
The
study explains on pages 144–145 that AI can strengthen supervision by
detecting irregularities earlier than manual systems.
Major
Challenges in AI Implementation
Despite
its promise, AI integration faces significant barriers.
Using
a Fishbone Analysis approach (illustrated in Picture 1, page 151), the
study categorizes challenges into six main areas:
🔹 Human Resources (Man)
- Limited
AI expertise
- Resistance
to technological change
- Need
for specialized training
🔹 Technology Infrastructure (Machine)
- Inadequate
hardware capacity
- Outdated
IT systems
- Integration
difficulties
🔹 Methods and Procedures
- Traditional
maintenance processes not yet data-driven
- Lack
of standardized AI-compatible procedures
🔹 Data (Material)
- Inconsistent
historical records
- Sensor
limitations
- Manual
inventory tracking
🔹 Work Environment (Environment)
- Organizational
culture not fully ready for digital transformation
- Regulatory
constraints
🔹 Leadership and Policy (Management)
- Budget
limitations
- Lack
of strategic vision
- Uncertainty
regarding long-term ROI
The
authors emphasize that AI success depends not only on technology, but also on
leadership commitment and organizational transformation.
Strategic
Benefits for National Defense
When
implemented systematically, AI offers major advantages:
- Increased
aircraft availability
- Reduced
operational downtime
- Improved
flight safety
- Lower
maintenance costs
- Enhanced
national defense readiness
The
study concludes that AI integration can significantly strengthen Indonesia’s
air defense capability if supported by:
- Infrastructure
investment
- Personnel
training programs
- Organizational
culture reform
- Strong
management leadership
Author
Profiles
- Janjang
Satya E.W. – Universitas
Republik Pertahanan
- Budi
Santoso- – Universitas
Republik Pertahanan
- Yulianto
Hadi- – Universitas Republik
Pertahanan
Research
Source
Satya E.W., J., Santoso, B., & Hadi, Y. (2026). The Development of Fighter Aircraft Maintenance Management Through Artificial Intelligence Technology to Support the Duties of the Indonesian Air Force. Contemporary Journal of Applied Sciences (CJAS), Vol. 4 No. 2, 137–156.
DOI: https://doi.org/10.55927/cjas.v4i2.133
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