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Peer-reviewed work.

Selected publications across sensor optimisation, IVHM, and diagnostic decision-making. Each entry includes venue, co-authors, a short plain-English summary, and a direct link to the published paper.

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2026

MOSOF with NDCI: A Cross-Subsystem Evaluation of an Aircraft for an Airline Case Scenario

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
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Commercial translation

Demonstrates MOSOF and NDCI working across multiple aircraft subsystems simultaneously — proving the method generalises beyond a single case. The result gives engineering teams a cross-subsystem sensor prioritisation tool, not just a per-system audit.

Cite (BibTeX)
BibTeX · suslu2026mosof
@article{suslu2026mosof,
  author    = {Suslu, Burak and Ali, Fakhre and Jennions, Ian K.},
  title     = {{MOSOF with NDCI: A Cross-Subsystem Evaluation of an Aircraft for an Airline Case Scenario}},
  journal   = {Sensors},
  volume    = {26},
  number    = {1},
  pages     = {160},
  year      = {2026},
  publisher = {MDPI},
  doi       = {10.3390/s26010160},
  url       = {https://www.mdpi.com/1424-8220/26/1/160}
}
2025

Normalised Diagnostic Contribution Index (NDCI) Integration to Multi-Objective Sensor Optimisation Framework — An Environmental Control System Case

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
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Commercial translation

Validated on the Boeing 737-800 ECS: smaller, lighter, and cheaper sensor configurations that match or exceed the diagnostic coverage of the reference design. The core engineering result: you can remove sensors without losing diagnostic quality, if you know which ones to remove.

Cite (BibTeX)
BibTeX · suslu2025ndci
@article{suslu2025ndci,
  author    = {Suslu, Burak and Ali, Fakhre and Jennions, Ian K.},
  title     = {{Normalised Diagnostic Contribution Index (NDCI) Integration to Multi-Objective Sensor Optimisation Framework -- An Environmental Control System Case}},
  journal   = {Sensors},
  volume    = {25},
  number    = {9},
  pages     = {2661},
  year      = {2025},
  publisher = {MDPI},
  doi       = {10.3390/s25092661},
  url       = {https://www.mdpi.com/1424-8220/25/9/2661}
}
2023

Understanding the Role of Sensor Optimisation in Complex Systems

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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Commercial translation

The foundational framing paper — establishes why sensor selection in complex systems is a multi-objective problem, not a single-axis cost-benefit. Useful background reading for engineering teams evaluating whether a more rigorous sensor selection method is justified for their programme.

Cite (BibTeX)
BibTeX · suslu2023sensoropt
@article{suslu2023sensoropt,
  author    = {Suslu, Burak and Ali, Fakhre and Jennions, Ian K.},
  title     = {{Understanding the Role of Sensor Optimisation in Complex Systems}},
  journal   = {Sensors},
  volume    = {23},
  number    = {18},
  pages     = {7819},
  year      = {2023},
  publisher = {MDPI},
  doi       = {10.3390/s23187819},
  url       = {https://www.mdpi.com/1424-8220/23/18/7819}
}

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Conference papers, presentations, and earlier work are catalogued on Google Scholar. The two entries above are the highest-impact peer-reviewed pieces from the doctoral programme.

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