Description

Product Overview

AIO-Core is an enterprise supervisory optimization intelligence platform engineered for continuous hydrocarbon refining and continuous process complexes. Sitting directly above existing Distributed Control Systems (DCS) and Model Predictive Control (MPC) layers, AIO-Core resolves the multi-million-dollar plan-to-plant margin gap that occurs when plant units operate against static linear targets while feedstocks, ambient conditions, and market prices fluctuate.

Designed for operations directors, chief process control engineers, and console operators, AIO-Core continuously ingests live plant telemetry, reconciles laboratory assays via inferential soft sensors, and recalculates optimal economic handle limits every one to five minutes against a live market and carbon price deck. To guarantee operational integrity, every candidate move is passed through a deterministic mathematical safety shield evaluated in under 50 milliseconds before reaching the operator advisory queue or supervised edge dispatcher. By combining non-linear margin optimization with verifiable safety boundaries, AIO-Core enables industrial facilities to capture verified yield expansion, reduce fired-heater energy consumption, and manage carbon liability without risking plant trips or destabilizing base regulatory control.

The Problem

Modern processing facilities operate under continuous thermodynamic and economic volatility. Crude slates, product cracks, natural gas tariffs, hydrogen costs, and carbon emission allowances move dynamically, yet refineries are steered using linear planning schedules and static MPC models. Because continuous processing exhibits severe non-linear dynamics—driven by heat exchanger fouling, furnace coking, and catalyst deactivation—linearized controllers degrade over time. Industry experience indicates that over 65% of industrial multivariable controllers are detuned or artificially clamped by operators to prevent oscillations, stranding assets far from true hydraulic and economic limits.

This operational disconnect manifests as chronic product giveaway, excessive fired-heater fuel burn, hydrogen downgrading to fuel gas, and suboptimal cut recovery, destroying between $0.30 and$0.75 per barrel of processed crude. Traditional Real-Time Optimization (RTO) packages have largely failed to close this gap due to multi-hour convergence latencies, rigid steady-state wait-time requirements, and numerical fragility. Furthermore, operations teams routinely reject autonomous optimization systems that act as opaque black boxes or lack certified, deterministic safety guarantees.

How the Product Solves the Problem

AIO-Core transforms plant economics by introducing an adaptive, non-linear supervisory intelligence layer that works in concert with existing automation infrastructure. Instead of attempting unconstrained direct valve manipulation or replacing reliable base control loops, AIO-Core operates supervisory adjustments to MPC handle limits and optimization targets on a 1-to-5-minute cadence.

Telemetry is continuously screened through an automated Data Quality Gate to detect frozen or invalid signals. Physics-grounded soft sensors infer unmeasured stream qualities in real time, with laboratory assays dynamically reconciling bias via adaptive state estimation. The economic solver optimizes yield, energy, and carbon metrics simultaneously, passing every candidate move through a deterministic safety shield that mathematically guarantees all physical, hydraulic, and metallurgical limits are honored. Advisories are presented with complete causal explainability and margin breakdown, providing console operators with the trust and verification needed to capture peak margins safely.

Problem-Solving Flow

Value Creation Model

AIO-Core creates quantifiable commercial value by systematically recovering lost processing margin across heavy industrial assets. Value is generated at the seam between market pricing and operational execution, allowing facilities to capitalize on favorable market spreads while reducing utility consumption and environmental liabilities.

Value Creation Table