Voyage Performance

Voyage intelligence, one view.

A vessel that arrives three days late may have been below CP speed, or above CP speed but routed through bad weather, or held by a charterer-induced port delay — and the appropriate conversation is different in each case. The pipeline resolves the ambiguity before the dispute starts.

Charter Party compliancegood-weather filterETA vs laycanclaim probabilityAIS positionweather routing

Three stages

Read CP terms  →  Filter to good-weather legs  →  Score deviation + claim probability

Read — Charter Party terms, noon-report stream (speed, FOC, weather), AIS position, Stormglass/NAVTOR weather feed.
Filter — separate good-weather legs from bad-weather and instructed slow-steaming legs. CP warranted performance only applies to the good-weather subset.
Score — speed deviation, FOC deviation, ETA vs laycan, claim probability composite.

Charter Party compliance — the central question

Most voyage analysis questions reduce to: “is the vessel performing within Charter Party?” The CP defines a good-weather envelope and a warranted speed-and-consumption profile within it:

GOOD WEATHER ENVELOPE (typical CP)
   Wind:    Beaufort ≤ 4
   Sea:     Douglas sea state ≤ 3
   Current: ≤ ±0.5 knot
   Swell:   ≤ 2 m

WARRANTED PERFORMANCE (within envelope)
   Speed:          14.0 kn laden / 14.5 kn ballast
   FOC at sea:     28.5 MT/day VLSFO
   FOC in port:     3.2 MT/day MGO

Deviation against the CP-warranted values:

ΔV   = V_actual − V_CP
ΔFOC = FOC_actual − FOC_CP

A negative speed deviation under good weather with a positive consumption deviation is the textbook underperformance pattern that drives owner-vs-charterer disputes. A negative speed deviation in bad weather isn’t a CP issue — the warranted speed doesn’t apply.

Worked example — MV POSUN

Voyage: Singapore to Rotterdam, 21 days at sea, laden.

Leg type	Days	Avg speed	Avg FOC	Notes
Good weather	14	13.2 kn	30.6 MT	Below CP (14.0 kn / 28.5 MT)
Bad weather	5	11.4 kn	32.8 MT	Excluded from CP calculation
Slow-steaming (instructed)	2	11.0 kn	27.4 MT	Excluded

Filtered to good-weather legs only:

Metric	Value
Good-weather coverage	67%
Mean speed deviation	−0.8 kn
Mean FOC deviation	+2.1 MT/day

Verdict: sustained underperformance under good weather — claim probability HIGH.

Pipeline actions:

Generates a CP-claim brief with per-leg numbers, weather classification, and deviation maths.
Routes to Commercial Operator (claim handling) and Technical Superintendent (root cause — fouled hull? Engine?).
Cross-references ME performance for engine condition signals and fuel oil for fuel-quality signals.

Under the hood

Good-weather filtering — implementation

def good_weather_legs(legs, cp_envelope):
    """Filter legs to those within CP good-weather definition."""
    out = []
    for leg in legs:
        if leg["wind_bf"]         > cp_envelope["wind_max"]:    continue
        if leg["sea_ds"]          > cp_envelope["sea_max"]:     continue
        if abs(leg["current_kn"]) > cp_envelope["current_max"]: continue
        if leg["swell_m"]         > cp_envelope["swell_max"]:   continue
        out.append(leg)
    return out

def cp_performance(good_legs, cp):
    """Mean deviation of speed and FOC under good-weather conditions."""
    if not good_legs:
        return {"verdict": "Insufficient good-weather data", "coverage": 0.0}
    n = len(good_legs)
    delta_v   = sum(leg["speed_kn"] - cp["warranted_speed"] for leg in good_legs) / n
    delta_foc = sum(leg["foc_mt"]   - cp["warranted_foc"]   for leg in good_legs) / n
    return {"delta_v": delta_v, "delta_foc": delta_foc, "coverage": n / len(legs)}

Coverage matters. A voyage with only 10% good-weather legs has too small a sample to support a CP claim either way — the pipeline reports coverage alongside the deviation.

ETA vs laycan tracking

Metric	Calculation
Projected ETA	Current position + remaining distance / projected speed
Time to laycan start	laycan_start − ETA
Time to laycan end	laycan_end − ETA

Condition	Verdict
ETA before laycan start with margin	Early — risk of demurrage if charterer not ready
ETA inside laycan	On-window
ETA after laycan end	Late — penalty exposure

The pipeline updates ETA every noon report — a TSI sees drift as it happens, not at port-call time.

Claim probability composite

P_claim = w1 × mean(|ΔV|) + w2 × mean(|ΔFOC|) + w3 × (1 − coverage_good_wx)

The third term protects against weak claims. Low good-weather coverage means insufficient data to support the deviation either way — the score reflects that.

P_claim band	Action
Low	Routine — log and continue
Medium	Owner brief — document for next charter
High	Active claim or counter-claim risk — engage commercial
Critical	Significant exposure — legal advisory

Slow-steaming and weather routing

Slow-steaming — a vessel deliberately running below CP speed for fuel saving looks like underperformance unless the CP allows it. The pipeline checks CP terms and master’s voyage instructions; if both agree, the leg is excluded from the deviation calculation.

Bad-weather routing — when a master chose a longer route to avoid weather, the voyage shows as longer at lower average speed. The pipeline cross-references FOC over the routed leg vs the rhumb-line projection — sometimes the longer route is the lower-cost option even though it looks slower on speed alone.

Data sources

Data	Source	Cadence
Position	AIS + noon report	Continuous + daily
Speed	Noon report	Daily noon-to-noon
FOC by grade	Noon report	Daily
Weather	Noon report + Stormglass + NAVTOR	Daily
Routing analysis	NAVTOR	Per voyage
Charter Party terms	CP file in vessel records	Per charter
ETA vs laycan	Voyage plan in ERP	Continuous

The CP file is re-read on every analysis run — changes mid-voyage are reflected immediately.

Escalation triggers

Trigger	Severity
Speed deficit > 5% under good weather, sustained 3+ legs	HIGH
Consumption excess > 5% under good weather, sustained 3+ legs	HIGH
ETA threatening laycan end	HIGH
Claim probability HIGH or CRITICAL	CRITICAL
Pattern across 3+ consecutive voyages	CRITICAL
Weather routing adding > 10% to passage time	per case