Stabilization (=reducing the variations) of essential process variables enables the process to operate closer to limits, where often the best performance is achieved.


We achieve stability by re-tuning existing controllers or by (slight) modification design of the existing control logic or by applying the advanced features available in modern process control systems.



It is necessary to know the behavior of the process when improving the process control. We use live data collection from process data historian, analysis and modeling in cases where we cannot directly conclude the behavior. This is what we call data and model based process control development.


We do process control review and development during the engineering phase of a new production process. Since live data is not available, we rely on process design data and our past experience.


Energy efficiency improvement is one important part of improving the bottom line. We take care of process control improvement in cases where process control has an essential impact on energy efficiency.


We guide the process engineers and operators to find more productive operational practices in addition to process control improvement.


Sometimes, a process may, after all, require Advanced Process Control (APC), Artificial Intelligence (AI) or Machine Learning (ML) solutions. In such cases, we will do a full-scale Study on the improvement potential, required solution architecture and solution cost estimates.