Smarter plant operations with Mechanistic AI

Close information gaps and optimize resource heavy operations such as distillation or hydrocracking

Too often operators are flying blind when operating critical process units: for instance, distillate samples are taken once or twice a day or catalyst effectiveness is unknown.

Mechanistic AI bridges information gaps, delivering real-time estimates of important unmeasured or delayed variables. It allows operators to optimize unit performance further adding millions of euros to the bottom line annually.

Traditional vs. Neural Networks vs. Mechanistic AI – Comparison

Category	Traditional	Data-driven	Mechanistic AI
Lifetime Cost	High > 1 M €	>500 000 €	Typically under 500 000 €
Approach	Manual/ first-principles	Black-box methods, regression, PLS	Grey-box
Data requirements	Low	Moderate to High	Very Low to Low
Accuracy / economic benefit	Low	Low to Moderate	High
Explainablity	High	Low	High
ROI period	Years	~1 Year	Few Months

The project aimed to create an advanced model by utilizing data in combination with physical and chemical principles, to be capable of estimating the purity of the bottom product in a distillation column. This model offered valuable insights into the column’s operations, revealing a deeper understanding of the underlying process. Scientia Industrial Technologies demonstrated extensive expertise in process technology throughout the project. They showcased their ability to gain a thorough understanding of the complexities within the distillation process and effectively integrate this knowledge into the model, allowing it to uncover relevant aspects.

Mohammed Adlouni

Senior Specialist, APC and Analytics

Perstorp AB

We recently collaborated with Scientia Industrial Technologies to analyze the improvement potential of our vacuum distillation column. Their team demonstrated exceptional process understanding and analytical skills, successfully identifying key factors leading to increased process profitability. We were impressed by their expertise and look forward to continuing our partnership on future projects.

Lukas Vikander

APC Engineer

FAQ

We provide an on-premise setup that eliminates the need for cloud integrations, ensuring full control over your data. The system deploys securely via the OPC UA platform, allowing smooth, protected data exchange. Additionally, ownership of the data remains entirely with you, and we never share it with any third parties.

As a fast-growing startup attracting strong market interest, we’re committed to long-term growth and stability. We provide yearly maintenance to keep your model updated and performing optimally, backed by dedicated specialists that ensure our solutions stay in sync with your evolving process needs.

Although your team will need to provide data and feedback, we handle most of the model-building process, offloading much of the workload away from you. This means your time commitment is limited to essential inputs and approvals. In return, you gain a comprehensive solution that integrates seamlessly with your existing workflows.

Mechanistic AI offers transparency through a “grey-box” design, combining data-driven techniques with real-world process knowledge. This hybrid approach lets you see how the model interprets your process behavior, unlike traditional black-box methods. As a result, you can validate predictions with confidence and gain clear insights into the system’s operation.

Smarter plant operations with Mechanistic AI

Traditional vs. Neural Networks vs. Mechanistic AI – Comparison

FAQ

Is My data secure?

How do you ensure business continuity?

Is this going to be a big project?

How can I trust the results?