2026
Sensors, 26(1), 160 · Suslu, B., Ali, F., & Jennions, I. K. · MDPI · 2026 · DOI: 10.3390/s26010160
A cross-subsystem evaluation applying the combined MOSOF + NDCI approach across Engine, Fuel, EPS, and Environmental Control subsystems for an airline-case aircraft. The published Pareto-front knee solution is just 12 sensors (Engine 5, Fuel 2, EPS 2, ECS 3) at approximately 0.69 normalised diagnostic performance — demonstrating that prioritising diagnostic contribution at the network level enhances detection and isolation without inflating sensor count.
Sensor optimisation
NDCI
MOSOF
Cross-subsystem
Aerospace
IVHM
2025
Sensors, 25(9), 2661 · Suslu, B., Ali, F., & Jennions, I. K. · MDPI · 2025 · DOI: 10.3390/s25092661
Introduces the Normalised Diagnostic Contribution Index — a per-sensor score for the share of system-level diagnostic coverage each sensor contributes. Integrates NDCI into the Multi-Objective Sensor Optimisation Framework (MOSOF) and validates the combined approach on an Environmental Control System case through Cranfield's SESAC platform. Result: smaller, lighter, cheaper sensor configurations that match or exceed the diagnostic capability of larger reference designs.
Sensor optimisation
NDCI
Aerospace
ECS
2023
Sensors, 23(18), 7819 · Suslu, B., Ali, F., & Jennions, I. K. · MDPI · 2023 · DOI: 10.3390/s23187819
A foundation paper for the sensor-optimisation thread of the doctoral research. Frames sensor selection on complex assets as a multi-objective problem rather than a single-axis cost-versus-coverage trade-off, and sets out the formal structure that becomes MOSOF in subsequent work. Reviews the gap between how sensor networks are designed in practice and what optimisation theory says they should look like.
Sensor optimisation
IVHM
Complex systems
MOSOF
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