High-value opportunities don’t unlock themselves
We use our deep refining and chemical processing expertise and Closed Loop Neural Network™ technology to facilitate pre-project research, conduct economic validation studies, and gain organizational alignment around high-value optimization strategies.
Generalized first-principle economic models
We have developed first-principle economic models which consider process constraints, operation modes, feeds, and products. We use these models to isolate the extrinsic and intrinsic economic variabilities, discover new optimization opportunities, and define your initial universal objective function.
Steady-state baseline models
Imubit’s team understands what we’re trying to do from an operating and an economics perspective. Their deep learning process technology and their approach have aligned everyone from planning and operations around a shared goal.”
– Process control and optimization manager
Unlocking profits at world-class plants and refineries, including:
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.