{
  "_meta": {
    "title": "Pareto front — B737-class cross-subsystem sensor optimisation",
    "source": "Suslu, B. (2025). Sensor Optimisation for Aircraft Health Management Systems. PhD thesis, Cranfield University, School of Aerospace, Transport and Manufacturing — IVHM Centre. Supervisor: Prof. I. K. Jennions; Associate Supervisor: Dr F. Ali.",
    "related_papers": [
      "Suslu, Ali, Jennions (2026). MOSOF with NDCI: A Cross-Subsystem Evaluation. Sensors 26(1), 160. doi:10.3390/s26010160",
      "Suslu, Ali, Jennions (2025). NDCI Integration to MOSOF — An ECS Case. Sensors 25(9), 2661. doi:10.3390/s25092661"
    ],
    "headline_figure": "Figure 4-17, p.188",
    "knee_source": "Table 4-5, p.190 — 12-sensor suite (Engine 5, Fuel 2, EPS 2, ECS 3)",
    "what_is_real": "Knee point (perf 0.69, cost $36k, MTBF 145 kh, suite split) is verbatim from Table 4-5. Axis ranges and front-shape regimes are from the prose around Figs 4-16..4-18.",
    "what_is_synthesised": "Per-point coordinates. The MOGA per-point output exists as bitmaps in Figs 4-16/17 only, not in the PDF text layer. Points are generated here to lie on a Pareto surface bounded by the published ranges and to pass through the published knee. The reliability axis follows series-equivalent MTBF: 1/Σ(1/MTBF_i), with sensor-family MTBF medians from Section 4.3.",
    "n_points": 77,
    "knee_composition": {
      "Engine": 5,
      "Fuel": 2,
      "EPS": 2,
      "ECS": 3
    }
  },
  "axes": [
    {
      "id": "performance",
      "label": "Diagnostic performance",
      "unit": "NDCI normalised",
      "direction": "max",
      "min": 0.2,
      "max": 0.71
    },
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      "id": "cost",
      "label": "Cost",
      "unit": "kUSD",
      "direction": "min",
      "min": 32.0,
      "max": 55.0
    },
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      "id": "reliability",
      "label": "Suite reliability",
      "unit": "MTBF (kilohours)",
      "direction": "max",
      "min": 88.0,
      "max": 350.0
    }
  ],
  "knee_index": 76,
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}