Dynamic plant process models and visualizations
We use our proprietary process modeling platform to build, verify and continuously improve your deep learning process models that run closed-loop in production. Working alongside your process engineers we identify the hidden governing dynamics between variables and refine, validate and build operator confidence in the models.
Process modeling platform
Deep learning process models
Dynamic relationships visualization
Imubit has completely transformed what I thought was possible in process control and optimization. Deep learning process control can truly understand and optimize the non-linear, highly dynamic relationships found in complex processes. Being able to predict and control these behaviors is going to forever change the process industry.”
– Process control team lead
Unlocking profits at world-class chemical 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.