Houston, Texas, October 16, 2024. ARC Advisory Group's 2024 Process Optimization and Controls Market Study treats closed-loop AI as its own group of process optimization and control technology, next to advanced process control (APC) and online optimization. The study includes Imubit's reinforcement learning approach. Our summary of the study covers how ARC separates the three groups and what it found on adoption.
Refiners at AFPM
On the same day, two U.S. refiners that run Imubit closed-loop applications presented at the American Fuel & Petrochemical Manufacturers (AFPM) summit in New Orleans. Both spoke about improving refinery margin by reducing product giveaway with closed-loop control.
How the technology works
In Imubit's Deep Learning Process Control® (DLPC®), a Deep Learning Predictor learns a nonlinear dynamic model of the unit from its own operating history, guided by first principles. A Deep Learning Controller, trained by reinforcement learning across millions of simulations, learns the control policy. The controller runs on-premise and writes targets to the existing APC or DCS minute by minute, inside limits set by plant engineers. It complements the control layers already in place.
Planning, process engineering, process control and operations work from the same model of the unit, so each group can see the result of a change before it is made.
About Imubit
Imubit brings Closed-Loop Physical AI to refining, chemicals and polymers, cement, and mining and minerals. The Imubit Platform maps plan-to-plant gaps to the recurring decisions behind them, models the causality with DLPC®, and takes the critical decisions to autonomous execution, inside limits set by plant engineers, on top of APC and DCS. Imubit is trusted by 7 of the top 10 U.S. refiners. The company was founded in 2016 and is headquartered in Houston, Texas.
