Real-Time Optimization (RTO) — SMHcoders
INDUSTRIAL AI // RTO-07

Real-Time Optimization

Plant-wide optimization that computes the most profitable operating targets for your MPC and APC systems.

// What it is

How Real-Time Optimization works for your plant

Real-Time Optimization sits above the control layer. Using a plant-wide model, current constraints and current economics, it computes the most profitable feasible operating point — and passes those targets down to your MPC and APC controllers to execute.

OPTIMIZATION STACK
RTO — PLANT-WIDE ECONOMICSPROFIT-OPTIMAL TARGETS
MPC / APC — CONSTRAINED MOVESEVERY CYCLE
DCS + PLANT — EXECUTIONFIELD
// How it works

From data to running system

01
Model

Plant-wide steady-state model built.

02
Reconcile

Model matched to live plant data.

03
Optimize

Most profitable feasible point computed.

04
Dispatch

Targets passed to the MPC/APC layer.

// Industries

Where it applies

Oil and GasPowerMining

“MPC holds the unit where you tell it. RTO decides where that should be — every hour, at today's prices.”

SMHCODERS · OPTIMIZATION
// Benefits

What it changes

RTO-07 // IMPACT BOARD
Profit-optimal targets, continuouslyOK Consistent operation across shiftsOK Adapts to prices and feed changesOK Builds on your MPC investmentOK
FROM THE FIELD

Your MPC holds the unit steady. RTO decides where steady should be — in money.

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// FAQ

Common questions

Do we need MPC before RTO?+

In practice, yes. RTO computes profit-optimal targets; MPC or APC is the layer that executes them. If you run MPC today, RTO is the natural next step.

What data do we need to start?+

Most engagements start with 6–24 months of historian, lab or document data. We audit coverage in the first week and tell you plainly if it is not enough — before you commit.

How long until we see results?+

A proof of concept on your historical data typically lands in 4–8 weeks. Production deployment follows once the KPI target is met and your team signs off.

Where does it run, and who sees our data?+

On your infrastructure — plant-side servers, your Azure or AWS tenancy, or an air-gapped network. Data never leaves your boundary, and nothing is used to train third-party models.

Who owns the result?+

You do. Handover includes source code, documentation, training sessions and a retraining plan.