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TwinCore™

Operating digital twins for plants, equipment, utilities, and fleets — test the decision before you make it.

TwinCore builds physics-informed digital twins of your operating assets and processes. Engineers and operators use them to simulate setpoint changes, debottlenecking moves, energy-saving strategies, and what-if scenarios before they touch the live process. No more 'we think this will work — let's try it on Sunday morning.'

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Who it is for

  • Process and reliability engineers tuning operating envelopes on critical equipment
  • Operations leaders evaluating debottlenecking and capacity moves
  • Energy managers chasing cost and emissions reduction without throughput loss
  • Engineering teams stress-testing new control strategies before deployment

The problem we are solving

Real plants are expensive labs. Engineers either run trials on the live process and absorb the risk, or build a one-off spreadsheet model that nobody trusts six months later. Neither answers 'what happens if we change this?' with confidence.

How it works

Build the twin from physics + your data

We combine first-principles models (heat and mass balance, hydraulics, electrical load, thermodynamics) with machine-learned residuals trained on your historian. The twin matches your plant's behavior, not a textbook plant's.

Validate against the last 12 months

Every twin is back-tested against at least a year of operating data. We publish the error envelope per key tag so users know exactly when to trust it and when to flag.

Run scenarios, ship insights

Operators and engineers use a browser UI to change setpoints, equipment configurations, or feedstock and see predicted throughput, energy, emissions, and reliability impact. Approved scenarios become operating procedures.

Measurable benefits

Ranges below reflect the low and high end of outcomes observed across pilots and production deployments. Your numbers will depend on your starting baseline.

4–11%
Energy reduction
from setpoint and load-balancing optimization
20–60%
Debottleneck CAPEX avoided
by sequencing soft moves before hardware
weeks → hours
Trial cycle time
simulate before committing the plant

Capabilities

  • Process twins for furnaces, reactors, distillation, grinding, smelting, utilities
  • Equipment twins for pumps, compressors, motors, turbines, conveyors
  • Plant-wide energy and utility twins (steam, compressed air, electrical)
  • Scenario library with versioning, approval workflow, and outcome tracking
  • Hooks back to control system for closed-loop advisory (where supported)
  • Continuous calibration as new operating data arrives

Integrates with

We connect to the systems you already run. No rip-and-replace.

PI System / AVEVA PI, Aspen Plus / HYSYSHoneywell Experion, Emerson DeltaV, ABB 800xASAP PM / Maximo for asset masterPython / Julia for custom physics modules

Proof point

A copper smelter used TwinCore to test 7 setpoint strategies on its anode furnaces, deployed the best two, and locked in a 7.8% gas consumption reduction with no throughput loss — payback in under 5 months.

Frequently asked

The questions buyers in your seat actually ask before committing to TwinCore.

Is this a 3D visualization or a real engineering model?
Real engineering model. TwinCore combines first-principles physics (heat and mass balance, hydraulics, electrical load, thermodynamics) with machine-learned residuals trained on your historian. Visualization is optional; the value is in predictive accuracy.
How do we know the twin actually matches our plant?
Every twin is back-tested against at least 12 months of operating data and we publish the error envelope per key tag. Users know exactly where to trust the twin and where to flag results for engineering review.
Can it write back to our DCS or PLC?
It can, but rarely should on day one. Most customers start in advisory mode — the twin recommends, the operator decides. Closed-loop integration with Honeywell Experion, Emerson DeltaV, ABB 800xA is supported once the scenario library is mature and governance signed off.
How does it stay accurate as the plant ages and feedstock changes?
Continuous calibration. New operating data flows in, residual models retrain on a schedule, and the error envelope is recomputed. If drift exceeds your tolerance the twin flags itself, rather than quietly going wrong.
Can we use it for operator training as well as engineering studies?
Yes. The same twin can run accelerated or paused for training scenarios — startup, upset, trip — without touching the live process. Several customers use it as a second-shift coaching tool.

Run the experiment in the twin first.

Pick one process or equipment system. We will deliver a validated twin and three answered what-if questions in 60 days.

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