> ## Documentation Index
> Fetch the complete documentation index at: https://docs.appliedaifoundation.org/llms.txt
> Use this file to discover all available pages before exploring further.
# Lube Oil Surveillance
> End-to-end pipeline that captures lube oil lab analysis, shore-sampling compliance, tank ROB, and consumption — flags wear-metal trends, contamination, and bunker planning gaps.
## Executive summary
Lube oil is the cheapest insurance policy on a vessel. A single sample tells a Technical Superintendent whether a bearing is wearing, whether seawater is leaking into the cooler, whether fuel is diluting the crankcase, whether the FW generator membrane is failing. Lube oil also moves through tanks: ROB management, bunker planning, and the cost of running out at sea — all driven by the same numbers.
The **Lube Oil Surveillance** pipeline tracks four parallel streams:
1. **Shore analysis results** — wear metals, additives, contaminants, TBN, viscosity from the lab
2. **Sampling compliance** — per-machinery sample dates, frequency, next-due, overdue flags
3. **Tank ROB & bunker planning** — distribution by tank, capacity, recommended intake to reach 85%
4. **Daily consumption** — AE crankcase oil from the consumption form, compared against maker limits
Together, the four streams answer the only three questions a TSI cares about: Is the equipment wearing? Are samples on schedule? And do we have enough oil onboard to reach the next bunker?
## Architecture
```
┌────────────────────────────────────────────┐
│ Lab feed · vessel forms · ROB inventory │
└─────────────────────┬─────────────────────┘
│ samples + tank data
▼
┌────────────────────────────────────────────┐
│ Stage 1 — Collection │
│ Per-vessel snapshot of lab batch + │
│ shore schedule + tank ROB + consumption │
└─────────────────────┬─────────────────────┘
│ structured evidence
▼
┌────────────────────────────────────────────┐
│ Stage 2 — Analysis │
│ • Wear-metal trends │
│ • Contamination flags │
│ • TBN reserve & viscosity drift │
│ • Sampling compliance vs schedule │
│ • Tank distribution & bunker planning │
│ • Daily consumption vs maker limits │
└─────────────────────┬─────────────────────┘
│ verdict + scores
▼
┌────────────────────────────────────────────┐
│ Stage 3 — Expert review │
│ Auto-escalate to TSI when triggered │
└────────────────────────────────────────────┘
```
***
## Stage 1 — Data collection
### Where the data comes from
The lube-oil pipeline pulls data from three independent surfaces and reconciles them:
| Source | What it provides |
| -------------------------------- | ------------------------------------------------------------------ |
| **Lab analysis (shore samples)** | Wear metals, additives, contaminants, TBN, viscosity per equipment |
| **Vessel-side LO forms** | Daily AE crankcase oil consumption + monthly lube-oil ROB |
| **ERP (LO inventory)** | Tank distribution, capacities, supplier records |
Lab analysis is sourced from any of the major marine lube-oil laboratories the vessel uses:
| | Laboratory | Specialty |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------ | -------------------- |
| 
| **Castrol** | Lab-mail integration |
| 
| **Chevron** | Lab-mail integration |
| 
| **Mobil Serv** (ExxonMobil) | Lab-mail + API |
| 
| **Shell** | Lab-mail integration |
| 
| **TotalEnergies** | Lab-mail integration |
| 
| **Gulf** | Lab-mail integration |
| 
| **Maritec** | Lab-mail integration |
| 
| **Marlab** | Lab-mail integration |
| 
| **VPS** — Veritas Petroleum Services | Lab-mail integration |
| 
| **Tribocare** | Lab-mail + API |
| 
| **Viswa Lab** | Lab-mail + API |
Most labs send results by email; the pipeline parses the lab report (PDF or structured email body) and normalises into the same shape regardless of source.
For each lubricated equipment (main engine system oil, cylinder oil, AE crankcase, hydraulics, gearboxes), the collector captures:
### Lab analysis
| Domain | Parameters |
| --------------- | --------------------------------------------------- |
| Wear metals | Fe, Cu, Pb, Sn, Cr, Al |
| Additive metals | Zn, Ca, Mg, P |
| Contaminants | Water, fuel dilution, soot, silicon |
| Oil condition | Viscosity at 40 °C and 100 °C, TBN, TAN, oxidation |
| Sample meta | Sample date, equipment running hours at sample, lab |
### Sampling schedule
Per machinery: sample frequency, last sample date, next-due date, due-status (Overdue / Due / In Order), test lab, report links, line items per past sample.
### Tank ROB
Per tank: grade, tank name, current ROB (litres), 100% capacity, 85% capacity, ullage, calculated bunker intake to reach 85%.
### Daily consumption
Per AE per day from the consumption form: crankcase oil consumption (L/day), running hours, comparison vs maker limit.
***
## Stage 2 — Analysis
### 2.1 Wear-metal trends
For each metal the analyzer computes period-over-period change:
$$
\dot{m} = \frac{m_n - m_{n-1}}{\Delta t}
$$
A step jump where $m_n > 2 \cdot m_{n-1}$ is treated as a discrete event, not noise — bearing wear, ring failure, contamination ingress are all step events; gradual rise across three samples is a different signature.
| Pattern | Likely cause |
| ------------------------- | -------------------------- |
| Iron rising, gradual | Liner / ring wear |
| Iron + chromium step jump | Ring failure |
| Copper rising | Bearing wear |
| Lead + tin rising | Big-end bearing wear |
| Aluminium present at all | Piston / piston-pin damage |
| Silicon above 25 ppm | Dirt / air-filter ingress |
### 2.2 Contamination flags
Each contaminant maps to a specific equipment risk:
| Parameter | Threshold | Risk |
| ------------- | ----------------- | ----------------------------------- |
| Water | Above engine spec | Cooler leak, condensation |
| Fuel dilution | $> 5\%$ | Injector leak, fuel-pump seal |
| Soot | Above engine spec | Combustion incomplete, ring blow-by |
| Silicon | $> 25$ ppm | Dirt ingress, air-filter failure |
### 2.3 TBN reserve and viscosity drift
TBN reserve is tracked against the fresh-oil baseline:
$$
\text{TBN reserve \%} = \frac{\text{TBN}_\text{current}}{\text{TBN}_\text{new}} \times 100
$$
Tier:
* $\geq 75\%$ — Healthy
* $50\% \leq \text{TBN reserve} < 75\%$ — Trend down, monitor
* $25\% \leq \text{TBN reserve} < 50\%$ — Oil change discussion
* $< 25\%$ — Overdue
Viscosity drift outside maker spec at either 40 °C or 100 °C indicates fuel dilution (drop) or oxidation (rise).
### 2.4 Sampling compliance
Per machinery, the analyzer enforces the sample frequency:
$$
D_\text{next} = D_\text{last} + F \quad \text{where } F \text{ is the configured frequency}
$$
$$
\Delta_\text{days} = D_\text{next} - D_\text{today}
$$
Status mapping:
| Verdict | Condition |
| -------- | -------------------------------- |
| Overdue | $\Delta_\text{days} \leq 0$ |
| Due Soon | $0 < \Delta_\text{days} \leq 14$ |
| In Order | $\Delta_\text{days} > 14$ |
The per-machinery view assembles the same shape across every lubricated component. Condensed:
```python theme={"system"}
formatted_row = [
row["machineryName"],
{"status": row["reportStatus"],
"color": status_to_color_mappping.get(row["reportStatus"], "grey")},
row["sampleDate"].strftime("%Y-%m-%d"),
row["nextDue"].strftime("%Y-%m-%d"),
row["frequency"],
{"status": row["dueStatus"],
"color": status_to_color_mappping.get(row["dueStatus"], "grey")},
row["testLab"],
report_links, # downloadable lab report
{"lineitem": lineitem[index]}, # historical sample list
]
```
A vessel that is consistently overdue on samples will eventually show the wear it failed to detect — sampling gaps are the leading indicator of analytical blindness, not just a paperwork issue.
### 2.5 Tank distribution & bunker planning
For each tank, the analyzer computes how much to bunker to reach 85% capacity (the safe operating headroom):
$$
\text{Bunker intake} = (0.85 \cdot V_\text{capacity}) - V_\text{current}
$$
where $V_\text{capacity}$ is the 100% tank capacity and $V_\text{current}$ is the current ROB. Negative intake means the tank is already above 85% — flag for ullage check.
The aggregate view collapses intake across all tanks per grade, then surfaces the recommended order quantity per grade for the next bunker call.
### 2.6 Daily consumption vs maker limit
For AE crankcase oil from the consumption form:
$$
C_\text{daily} = \frac{V_\text{consumed (L)}}{H_\text{running}} \quad \text{[L/h]}
$$
Compared against the maker's specification limit:
$$
\text{Variance \%} = \frac{C_\text{daily} - C_\text{spec}}{C_\text{spec}} \times 100
$$
Sustained variance above 20% signals piston-ring blow-by or excessive cylinder feed-rate — both are top-end overhaul candidates.
### 2.7 Equipment-pattern correlation
The analyzer cross-references LO trends with equipment running hours and recent overhauls — wear after a recent overhaul is break-in; sustained wear well into a service interval is accelerated degradation. Cylinder cylinder uniformity findings on the [main engine](/skills/me-performance) often confirm or rule out a wear-metal trend on the same engine.
***
## Worked example
**Vessel**: `MV POSUN`, MAN 6S60ME-C main engine.
After a refresh:
| Equipment | Sample | Findings |
| --------------- | ---------------------- | ------------------------------------------------------------------ |
| ME system oil | 2026-04-12 | Iron 42 → 68 ppm (+62% step), silicon 8 ppm — bearing wear suspect |
| ME cylinder oil | 2026-04-08 | TBN reserve 48% — trend down; flag for change |
| AE1 crankcase | 2026-04-15 | Fuel dilution 3.2% — within range |
| AE3 crankcase | sample overdue 38 days | analytical blind spot |
| Hydraulics | 2026-03-20 | OK |
**LO tank ROB**:
| Grade | ROB (L) | 85% capacity (L) | Bunker intake (L) |
| ------------ | ------- | ---------------- | ----------------- |
| ME system | 8,400 | 12,750 | 4,350 |
| Cyl oil | 18,200 | 21,250 | 3,050 |
| AE crankcase | 1,250 | 1,275 | 25 |
**Verdict**: HIGH — ME system oil iron step-jump combined with sample overdue on AE3 means the analyzer is missing data on one engine while another shows accelerating wear.
The pipeline:
1. Tags the run with `escalation_required: true`
2. Updates the case to `awaiting-tsi-review`, priority CRITICAL
3. Sends an A2A message to the TSI inbox with the wear-metal evidence and the bunker-planning view
**Recommended actions**:
1. Investigate ME system oil iron step-jump — pull bearing inspection at next port.
2. Schedule AE3 LO sample within 48h — restore sampling cadence.
3. Plan ME cylinder oil change at next port — TBN reserve below 50%.
4. Bunker request: ME system 4,350 L, cylinder 3,050 L; AE crankcase already at 85%.
***
## Output deliverables
* **Executive summary** — overall LO posture, headline flags
* **Per-equipment lab table** — wear metals, additives, contaminants, TBN, viscosity
* **Wear-metal trend chart** — period-on-period rate of change per metal
* **Contamination findings** — per equipment with likely cause
* **TBN & viscosity status** — reserve %, drift direction
* **Sampling compliance** — per machinery, next due, overdue list, link to lab report
* **Tank ROB & bunker plan** — per grade, recommended intake to reach 85%
* **Daily consumption** — AE crankcase oil vs maker limit
* **Equipment correlation** — recent overhauls, running hours, ME / AE cross-reference
* **Recommendations** — prioritised by impact, with timeline
* **Escalation decision** — auto-routed to TSI when triggered
***
## Escalation triggers
| Trigger | Severity |
| ---------------------------------------------- | -------- |
| Wear metal above CRITICAL threshold | CRITICAL |
| Step jump in any wear metal | HIGH |
| Water above engine spec | HIGH |
| Fuel dilution above 5% | CRITICAL |
| TBN reserve below 25% | HIGH |
| Sample overdue more than 30 days | HIGH |
| Daily consumption variance above 20% sustained | HIGH |
| Tank ROB below safety reserve with no stem | CRITICAL |
***
## Why script-driven
Wear-metal rate maths, TBN-reserve calculation, sampling-frequency arithmetic, and bunker-intake formula all live in deterministic Python. The reviewer interprets the result; verdicts are reproducible. A wear-metal trend that flips from "monitor" to "escalate" between two samples is a real change in the data, not a model decision.
Sample compliance and lab analysis matter together. A vessel sampling on time but ignoring the trend is not better than a vessel skipping samples — both end with the same engine overhaul. The pipeline reports both streams in the same review so the TSI sees them together.
***
## References
Lube-oil-analysis suite — shore-analysis status and tank distribution & bunker planning.
Performance-analysis suite — AE LO consumption, shore-analysis data, and shore-analysis scheduling.
Wear metals confirm or rule out cylinder findings on the main engine.
Crankcase oil consumption is the top-end overhaul leading indicator for AEs.