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: Inconsistent product composition makes it difficult to maintain reliable control or find the root cause of variations.
- Slow Response to Changing Conditions: Feedstock variations or catalyst deactivation create disturbances which APCs can’t always properly handle.
- Limited Economic Optimization: While APC achieve certain economic benefit, it rarely has the insights needed to maximize profitability to the fullest extent.
- Dependency on Faulty Analyzers: When key analyzers go offline or deliver poor-quality data, APC systems lose visibility into critical variables – disrupting control and reducing 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.