Now live: a hybrid process digital twin for amine gas sweetening — it names the fault and the root cause, not just the alarm. Explore the platform →

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Live Diagnosis

Detect

Live in the platform

Name the fault. Name the cause. Price the consequence.

Detect turns residuals into a diagnosis. Not "something looks abnormal" — a named fault with a confidence, the root cause behind it, the indicators that made the call, and what it is costing you per hour while it runs.

22Named fault signatures
19Root causes mapped
54Diagnostic indicators
6Costed consequences

What it does

Four things it does that a dashboard does not.

01

Named faults, not anomalies

Absorber and stripper foaming. Absorber and stripper flooding. Exchanger fouling and internal leak. Reboiler fouling, corrosion and tube leaks. Pump cavitation on all four pumps. Under-stripping. Filter plugging and bypass. Inlet conditioning failure. Each one is a signature with its own evidence, not a threshold on a tag.

02

Root cause, with the reasoning shown

Thermal degradation, heat-stable salts, hydrocarbon contamination, suspended solids, wrong antifoam, duty deficiency, internals damage, control-loop instability. Every attribution lists the indicators that witnessed it, the ones that corroborate, and the ones that would exonerate it.

03

A cost, not just a colour

Six consequence buckets: off-spec treated gas, amine losses, excess steam and energy, reliability and availability loss, and throughput given away to hold spec. Each active fault carries a severity and a nominal cost per hour, so the shift can rank what to fix first.

04

It knows when not to speak

Transients and off-baseline load are gated out before anything is judged. A plant that is ramping is not a plant that is faulty, and a diagnostic engine that cannot tell the difference is noise.

How it works

The pipeline, end to end.

  1. 1

    Gate the operating mode

    Load envelope, baseline deviation and steadiness are checked first. Unsteady rows do not reach the inference stages.

  2. 2

    Compute 54 indicators

    Level, trend and oscillation flavours, drawn from raw tags and from the reference model residuals over a six-hour trailing window.

  3. 3

    Fuzzify against fixed states

    Each indicator gets a membership in absolute engineering-unit states. After expert review most indicators were moved off relative sigma anchoring — a plant that is slowly getting worse must not quietly redefine what "normal" means.

  4. 4

    Match 22 fault signatures

    Primary evidence, corroborating evidence and exonerating context combine into a confidence and a tier: confirmed or suspected.

  5. 5

    Attribute the root cause

    Witness indicators point at a cause. Latent propensities — degradation, salts — act as priors, so a slow background problem raises the odds of the fast fault it eventually produces.

  6. 6

    Cost the consequences

    Active faults are mapped through the causal graph onto the six cost buckets, with a nominal figure per hour.

Under the hood

The engineering, stated plainly.

Every figure on this page is countable in the delivered system. If you want to see where a number comes from, ask us and we will show you the record it is read from.

Inference
Fuzzy signature matching over graded indicators
Anchoring
Fixed absolute engineering-unit state centres
Causal map
247 mapped edges across faults, causes and consequences
Context window
6 h trailing, for trend, oscillation and gating
Discipline
Calibration baked from training history; queries run on unseen data
Output
Fault · confidence · tier · cause · indicators · consequences · cost/h

What it does not do

The limits, published on the same page as the promise.

  • Twelve blind spots are declared on the platform, not hidden. There is no oxygen or blanketing tag on the storage tank, no reboiler skin temperature, no instrumentation on the condensate drum, and no analyser that can see trace surfactants arriving with the feed. Each one is published with what to watch instead.
  • Two indicators depend on a laboratory column or a sensor that is not yet installed. They are marked as external rather than quietly estimated.
  • Antifoam dose is a manual operator action, so it corroborates foaming — it can never trigger it alone. Removing that shortcut stopped a circular feedback loop where the operator's own response was being read back as proof of the fault.
  • The engine diagnoses. It does not act. Nothing is written back to the control system.

Where it applies

Built for amine systems today. Not limited to them by design.

The platform is focused on acid gas removal — gas sweetening and post-combustion carbon capture — because that is where the model is calibrated and where the fault library is real. The method underneath is not amine-specific: a physics reference model, residuals against expected-healthy, fuzzy diagnosis over graded indicators, and costed consequences. Extending it to another unit means new datasheets and a new calibration, not a new platform.

  • Gas sweeteningLive today
  • Post-combustion carbon captureLive today
  • Other acid gas removalMethod applies
  • Wider process unitsFuture

The fastest way to judge this is to open it.

The platform runs on a real amine train with thirteen days of one-minute history behind it. Nothing on these pages is a mock-up.

Open the platform