DEEP LEARNING PROCESS CONTROL
Automate real-time process adjustments
Go beyond open-loop recommendations and maximize your profitability with real-time, cross-unit process optimization
Closed-loop process optimization platform
Your truly dynamic controller is deployed and integrated to make real-time, cross-unit adjustments to optimize your objective function in the face of ever-changing feed compositions, product prices, and operational constraints. Our closed-loop optimization technology is truly dynamic, supports any process control or advanced process control footprint, and gives your engineers the required confidence in the predictive accuracy of your pre-optimized dynamic controller.
Pre-optimized dynamic controller
Process control network software
Imubit is not like other optimization software. Their user-friendly screens allows me to see what the optimizer is doing and the intuitive prediction plots mean that I always understand which moves the unit will make. Having an accurate prediction of my most critical target has completely changed the way I operate the unit.”
– Control board operator
An interconnecting neural network aligns all teams and stakeholders
lmubit is built for hydrocarbon processors who are looking for new ways to unlock margin from their assets. Unlike AI solutions that are bolted onto your existing methodologies, procedures and technologies, Imubit’s Closed Loop Neural Network™ crosses process unit and plant area boundaries. It flows through the traditional layers and interconnects all of the various teams. This allows everyone to speak the same language and drive towards a common economic goal. It manipulates carefully selected key variables by interconnecting real-time product prices with process constraints and economically critical properties. Instead of each team managing its own model in a discrete stack layer, all of the various disciplines interface with the Closed Loop Neural Network™.
Planning and economics feed direct real-time product and feedstock prices directly into the neural network. Process engineers input true unit operational constraints along with known process relationships. Process control engineers manage the interaction between the neural network and the existing advanced process control (APC) and distributed control system (DCS). Operators interact with the neural network on a 24/7 basis, constraining it to their desired bounds and limits in real time to allow for a safe and compliant closed-loop operation.
Hydrocarbon processing expertise
Deep reinforcement learning
Our interconnected AI solution is built on a deep reinforced learning architecture that uses your minute-by-minute data for real-time process optimization.