The chemical process landscape is rapidly evolving. Many refineries rely on Advanced Process Control (APC) to optimize their distillation columns, but run into one big issue – missing or incomplete data. Expensive simulators and traditional modeling approaches haven’t solved this challenge effectively.
Chemical Process Industry
Common Refinery Challenges
- Unstable Product Quality: Feedstock variation and other unmeasured disturbances make it difficult to maintain stable product quality.
- Limited Economic Optimization: While APC achieve certain economic benefit, it rarely has the insights needed to maximize profitability to the fullest extent.
- Dependency on Lab Sampling or Faulty Analyzers: APC systems lose visibility into critical variables due to unreliable analyzers or their complete absence significantly reducing plant performance.
How Mechanistic AI Helps
Mechanistic AI estimates unknown variables -like product composition or catalyst health – and delivers these insights directly to your DCS/PLC via OPC UA. This added layer of clarity helps APC respond faster to fluctuations and opens the door to real economic optimization.
Unlike costly simulators or purely data-driven models, our solution efficiently combines process knowledge with machine learning to deliver actionable, transparent results.
Mechanistic AI can help refineries to achieve
Facing similar challenges?
High operational costs, unpredictable plant behavior, or frequent APC adjustments – Mechanistic AI can bridge those gaps and unlock your plant’s full potential.