Imubit’s Optimizing Brain™ is enabling refiners and petrochemical manufacturers to accelerate decarbonization goals.
By Allison Buenemann, Imubit Product Marketing Manager
We just wrapped up an exciting week at Euro Petroleum Consultants’ Energy & Sustainability Forum in Madrid. Imubit Economic Engineer Dennis Rohe delivered a session focused on the role of AI optimization technologies in accelerating the energy transition. A packed house in the final hours of the conference demonstrated the importance of this topic to an audience of critical energy industry players.
Back at the booth, leaders from ENI, Total, MOL, OMV, and others dared to duel, pitting their team’s process expertise against Imubit’s Closed Loop Neural Network simulator. The AI simulator went undefeated and made believers of the conquered. Don’t worry, they went home the smiling, proud new owners of Imubit’s signature Engineer versus AI T-shirts.
ESF participants from ENI pose with their Imubit T-shirts after completing the optimization duel.
Imubit Economics Engineer Dennis Rohe engages in a panel discussion on how technology is enabling decarbonization in refining.
An Optimizing Brain™ that goes beyond financial objectives
The objective of closed loop optimization applications is typically to maximize profitability, represented by an economic objective function that leverages the unit mass balance to compare the value of the products with the cost of the feeds. However, as sustainability objectives increase in priority, additional considerations must be built into the objectives.
Progressing sustainability objectives like reducing energy consumption or overall carbon intensity of processes doesn’t come without business tradeoffs. With a clever objective function, constraint setting, and the right technology, you can reduce carbon footprint while allowing your business to remain in business.
AI optimization is already delivering
A 2023 McKinsey study found that AI leaders outperformed industry peers by a factor of 3.4x. Our experience echoes this. In the energy and chemicals sectors, the words “closed loop AI” used to ignite fear. To alleviate this fear, companies tried to lean into AI, but in open loop. The feasibility of an operator adjusting dozens of setpoints every few minutes based on model recommendations was quickly disproven. To ease fear while maintaining optimization potential, the approach has shifted to pre-trained on-site controllers, where the trained AI model is embedded rather than live-calculated via cloud compute.
A deployment of Imubit’s closed loop AI at one of the world’s leading recyclers or refinery byproducts generated a 15-30% reduction in natural gas usage while maintaining product quality, and actually increasing yield by 2%. In the complex, interdependent world of hydrocarbon processing, AI can quickly parse through the hundreds of thousands of operating scenarios to recommend the ideal process optimization move, making the sometimes non intuitive decisions that can ensure a sustainable, profitable, and long-lasting business.
Learn more
Weren’t able to catch our talk in Madrid? Join one of our upcoming webinars to see how Imubit’s Optimizing BrainTM approach can put you on a path to achieving your company’s sustainability pledges.
Upcoming Webinar Series
One Reality, One Model, One Goal:
An Optimizing Brain™ to Accelerate the Energy Transition
Is the Optimizing Brain™ the solution your plant needs? Discover why this pioneering approach
deserves your consideration. Don’t miss the opportunity to gain valuable insights and receive answers to your questions during the live Q&A session.
Available during these two date and time options:
Wed, Mar 20, 2024
1pm GMT | 2pm CET | 3pm EET
Register here
Wed, Mar 27, 2024
10am PST | 12pm CST | 1pm EST
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