Fuel Oil Analysis

Every fuel-borne risk, scored.

A vessel running 35 tonnes of HSFO a day is also running every gram of sulphur, every milligram of cat fines, every drop of water that came with the fuel. The lab report arrives 5–7 days after the fuel is in the tank — by then half of it is already in the engine. This pipeline turns bunker data, lab results, and ROB position into a TSI-grade view of what’s about to happen, not what already did.

cat finessulphur complianceROB planningconsumption variancestem timing

Three passes

Per-bunker quality  →  Tank distribution & ROB  →  Consumption variance

Each pass produces its own verdict; the three compose into the senior-review disposition.

Where the data comes from

Stream	Source	What it tells us
Bunker analysis	BDN + independent lab report	Per-bunker quality: viscosity, density, sulphur, cat fines, water, sediment
Tank ROB	Latest noon report (12:00 UTC)	Current quantity per grade, per tank
Daily consumption	Noon-report stream	Burn rate per grade, normalised to engine load and weather
Stem schedule	Bunker plan in ERP	Next bunker port, supplier, expected quantity
Vessel ECA exposure	Voyage plan	Whether the next leg is in an Emission Control Area

Labs used: Bureau Veritas / VeriFuel, VPS, Maritec, Tribocare, Viswa Lab, FOBAS. Results arrive by email after the bunker is sampled at delivery; the pipeline parses each lab report and reconciles against the BDN.

Fuel grades tracked: HSFO, VLSFO, ULSFO, MDO, LSMGO, LNG.

The thresholds

Cat fines (Aluminium + Silicon)

Cat fines are catalyst fines from the refining process — silicon and aluminium oxides hard enough to score liners, rings, and fuel pumps. ISO 8217 caps them at 60 mg/kg in the delivered bunker. Engine makers want 15 mg/kg or below at the engine inlet; fuel treatment can reduce 60 → 15 only if centrifuges are working perfectly.

Threshold	Status	Action
≤ 15 mg/kg	Safe	Routine
15–60 mg/kg	Risky	Confirm centrifuge effectiveness, monitor closely
> 60 mg/kg	Critical	Debunkering candidate — engine-damage risk

Sulphur — BDN vs lab

ISO 8217 sulphur caps: 0.50% m/m globally, 0.10% m/m in ECAs. Two checks run in parallel:

BDN compliance — the supplier’s declared sulphur must be at or below the operating cap.
Lab confirmation — the independent test must confirm the BDN within tolerance.

Discrepancy % = |S_lab − S_BDN| / S_BDN × 100

Above 5% triggers a supplier dispute flag.

Viscosity, density, water, sediment

Viscosity (cSt at 50 °C) and density (kg/m³ at 15 °C) determine whether the engine’s fuel system can handle the fuel. Too viscous and the heater can’t drop it to injection viscosity; too dense and centrifuge separation efficiency falls. Water above 0.5% v/v is corrosive; sediment above 0.10% m/m clogs filters and erodes pumps.

ROB safety reserve

Days of fuel = ROB / C_daily

Days remaining	Tier
< 7 with no stem arranged	CRITICAL
7–14 with stem more than 7 days out	HIGH
14–30 — routine planning	MEDIUM
> 30	OK

Per-bunker disposition

Disposition	Trigger
Accept	All parameters Safe
Monitor	One or more Risky, none Critical
Blend	Risky on cat fines or sulphur where mixing with cleaner stock can dilute below threshold
Debunker	Any Critical, especially cat fines > 60 mg/kg
Dispute	BDN-vs-lab sulphur discrepancy above 5%

Bunker planning formula

Bunker intake (to 85%) = (0.85 × V_capacity) − V_current

A tank already above 85% gets flagged for ullage check rather than further loading. Aggregated across grade gives the recommended quantity for the next bunker call.

Consumption variance

Variance % = (C_actual − C_design) / C_design × 100

Sustained variance over 10% is flagged. Combined with the main engine SFOC analysis, the analyzer can usually distinguish a fuel-quality cause (consumption + cat fines) from an engine-condition cause (consumption + cylinder asymmetry).

Worked example — bad bunker on MV POSUN

POSUN took on 480 tonnes of VLSFO at Singapore on 2026-04-12. The lab report arrives on 2026-04-19, mid-passage to the Suez Canal — already burning the fuel.

Parameter	BDN	Lab	Verdict
Cat fines (Al+Si)	24 mg/kg	74 mg/kg	Critical
Sulphur (% m/m)	0.42	0.46	Compliant, within discrepancy tolerance
Viscosity (cSt @ 50 °C)	380	385	Within engine spec
Water (% v/v)	0.30	0.35	Within tolerance

Verdict: Critical — cat fines 14× above the 15 mg/kg engine-inlet target and 23% above the 60 mg/kg ISO cap.

The pipeline tags escalation_required: true, routes the case to the Technical Superintendent and Commercial Operator, and generates three options:

Debunker at next port — cleanest, supplier dispute follows. Est. USD 30–50k port costs + supplier credit recovery.
Blend with clean VLSFO at 1:3 ratio — reduces engine-inlet exposure to ~18 mg/kg with reliable centrifuge operation. Requires 1,440 tonnes of clean stock at next port.
Run with maximum centrifuge cleaning + frequent fuel-system inspection — operational risk highest, cost lowest. Not recommended.

Under the hood

Cat-fines fleet split — implementation sketch

risky_threshold = 15                                 # mg/kg
risky_df = df[df["aluminium+Silicon"] > risky_threshold]
safe_df  = df[df["aluminium+Silicon"] <= risky_threshold]

fig.add_trace(go.Scatter(name="Safe CatFine Level",  x=safe_df.imo,
                         y=safe_df["aluminium+Silicon"], mode="markers"))
fig.add_trace(go.Scatter(name="Risky CatFine Level", x=risky_df.imo,
                         y=risky_df["aluminium+Silicon"], mode="markers",
                         marker=dict(color="red")))
fig.add_trace(go.Scatter(y=[15] * len(totaldf),
                         mode="lines", line=dict(color="red", dash="dot")))

BDN-vs-lab sulphur compliance check

def evaluate_sulfur(row,
                   bdn_sulfur_unit: str = "% m/m",
                   sulfur_unit:     str = "% m/m"):
    if row["sulfur"] is None or row["bdnSulfur"] is None:
        return "No Data"
    discrepancy = abs(row["sulfur"] - row["bdnSulfur"]) / row["bdnSulfur"] * 100
    if discrepancy > 5:
        return "Dispute"
    if row["sulfur"] > REGULATORY_CAP[row["zone"]]:
        return "Non-compliant"
    return "Compliant"

ROB aggregation — noon report only, from 715k records

json_rob = list(common_consumption.aggregate([
    {"$match":   {"IMO No": {"$in": active_imos}}},
    {"$addFields": {"reportTime":
        {"$dateToString": {"format": "%H:%M:%S", "date": "$Report Date"}}}},
    {"$match":   {"reportTime": "12:00:00"}},     # noon report only
    {"$sort":    {"IMO No": 1, "Report Date": -1}},
    {"$group":   {"_id": "$IMO No", "latestRecord": {"$first": "$$ROOT"}}},
    {"$replaceRoot": {"newRoot": "$latestRecord"}},
]))
# 715K records → one record per active vessel

Escalation triggers

The pipeline routes to the Technical Superintendent and the Commercial Operator simultaneously when fuel quality fails — fuel disputes are technical and commercial in equal measure.

Trigger	Severity	Owner
Cat fines above 60 mg/kg	CRITICAL	TSI + Commercial
Quality issues requiring debunkering	CRITICAL	TSI + Commercial
ROB critical with no stem arranged (under 7 days)	CRITICAL	TSI + Commercial
Sustained consumption variance above 10%	HIGH	TSI
Sulphur breach in ECA	CRITICAL	TSI + Commercial + Master
BDN-vs-lab sulphur discrepancy above 5%	HIGH	Commercial

Why this pipeline exists

A vessel without this pipeline finds out about a bad bunker when the engineers complain about filter blockages — usually two weeks after loading, with several hundred running hours already on the engine. With the pipeline, the lab report and BDN are reconciled within hours of arrival, the disposition decision is auto-routed, and the cost of doing nothing is calculated against the cost of acting.