Add OARMP routing engine, dashboard and documentation

- Complete routing engine: ingest, optimizer (CG+B&B), maintenance
  monitor, metrics, pipeline, quality checks
- Streamlit dashboard with Input/Output tab structure, editable data
  editors, interactive Folium map with satellite layer and maintenance
  base highlights, FH stacked bar chart with TTM availability
- CSV data files: AERONAVES, CHECKS, AIRPORTS, ESCALA DE VOO
- README, CONTEXTO and CHANGELOG added
- Remove legacy pre_process scripts and raw binary files (PDFs/xlsx)
- Update .gitignore to exclude outputs/, data/, raw/*.pdf, raw/*.xlsx

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

scripts/02_build_fleet_reference.py

@@ -0,0 +1,64 @@
+"""
+Script 02 – Build fleet reference table.
+
+Reads AERONAVES.csv + CHECKS.csv, computes TTM and the full check-cycle
+sequence for each aircraft, and saves the reference to data/reference/.
+"""
+
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(ROOT))
+
+import pandas as pd
+from datetime import datetime
+
+from src.routing_engine.config import DEFAULT_CONFIG
+from src.routing_engine.inspect_files import read_aircraft, read_checks
+from src.routing_engine.ingest import build_fleet, _check_cycles
+
+cfg = DEFAULT_CONFIG
+
+aircraft_df = read_aircraft(cfg.raw_dir / cfg.aircraft_file)
+checks_df = read_checks(cfg.raw_dir / cfg.checks_file)
+
+print("Aircraft loaded:")
+print(aircraft_df.to_string(index=False))
+print()
+
+print("Checks loaded:")
+print(checks_df.to_string(index=False))
+print()
+
+# Build fleet
+planning_start = datetime(cfg.planning_year, 3, 18)  # first OFRAG departure in the sample data
+fleet = build_fleet(aircraft_df, checks_df, planning_start)
+
+print("Fleet reference:")
+for _, row in fleet.iterrows():
+    print(f"\n  {row['tail_number']}  ({row['model']})  FH total = {row['fh_total']:.0f}")
+    print(f"    TTM before first check: {row['ttm_hours']:.1f} FH")
+    for i, c in enumerate(row["checks"]):
+        print(f"    Cycle {i}: threshold={c['fh_threshold']:.0f} FH, "
+              f"TTM={c['ttm']:.0f} FH, duration={c['duration_hours']:.0f} h")
+
+# Save to reference
+cfg.reference_dir.mkdir(parents=True, exist_ok=True)
+out_path = cfg.reference_dir / "fleet_reference.csv"
+
+flat_rows = []
+for _, row in fleet.iterrows():
+    flat_rows.append(
+        {
+            "tail_number": row["tail_number"],
+            "model": row["model"],
+            "fh_total": row["fh_total"],
+            "ttm_hours_cycle0": row["ttm_hours"],
+            "n_check_cycles": len(row["checks"]),
+            "cycles_json": str(row["checks"]),
+        }
+    )
+
+pd.DataFrame(flat_rows).to_csv(out_path, index=False)
+print(f"\nFleet reference saved -> {out_path}")