Chemical plants increasingly rely on digital intelligence, including advanced process control, real-time optimization, and digital twins. These systems promise a powerful capability: using models of the plant to continuously improve performance. By combining process data with physical and empirical models, they identify operating points that maximize efficiency, throughput, or energy utilization.
When the model is calibrated
These models rely on simplifying assumptions about heat transfer coefficients, friction factors, catalyst activity, and equipment performance curves.
When the model is calibrated, these parameters are usually accurate.
But plants do not remain static.
When the plant changes but the model does not
During operation, equipment slowly degrades:
- Heat exchangers foul
- Catalysts deactivate
- Hydraulic resistances increase
These changes alter the parameters that digital models rely on. Yet many optimization models remain fixed. Over time, the digital plant and the physical plant begin to diverge. The model still describes the plant as clean and ideal. The real system is slowly drifting away from those assumptions.
Digital maturity
Optimization algorithms are extremely effective at navigating the model they are given. But precision inside a model is not the same as accuracy in the plant.
As equipment degrades and parameters drift, optimization may steer the system toward operating points that appear optimal digitally but are less robust physically. This raises a broader question about what actually drives plant performance.
The model remains confident, while the plant slowly diverges from the assumptions behind it.
Digital maturity means closing that gap.
If degradation can be continuously measured, model parameters can evolve as fouling progresses, catalysts age, and hydraulics change. The digital twin then stops being a static snapshot.
It becomes a living representation of the plant.
The risk of false optimization
Without that feedback loop, digital precision can easily create a false sense of optimization.
