SCA's sawmill in Bollsta: "Without SenseNode, we would have discovered the problem when it was too late"

SCA's Sawmill: "Without SenseNode, we would have discovered the problem when it was too late."

SCA's sawmill in Bollsta is one of the largest in Sweden, with a total of 50 wood dryers. When operations engineer Jimmy Sehlberg needed a deeper understanding of the facility's energy usage, he reached out to SenseNode for assistance with metering. A test installation of meters on one of the dryers was conducted. Thanks to the insights gained from the energy measurements, they were able to improve the ventilation process and, consequently, the quality of the drying. New meters are now being installed to continue enhancing quality and increasing energy efficiency.

Quality Improvement from Day One

The installation of the meters was completed faster than expected. "It was a simple and successful startup phase," says Jimmy. As data from the dryer began to flow in, the team noticed a varying pattern in the dryer fan's performance. By comparing this data with the control system signals, deviations in the fan's programming were identified. The fan, which is supposed to periodically switch blowing direction, was less effective in one direction. The problem was traced back to a hatch that wasn’t closing properly, causing the air to not follow the desired path through the wood.

"Without SenseNode, we would have discovered the problem when it was too late."

The issue was resolved before it could lead to a decline in quality. "Without SenseNode, we would have discovered the problem when it was too late," says Jimmy. In addition to improving the wood quality, the action also prevented loose metal parts from entering the dryer, which could have had serious consequences.

Power Curve for the Chamber Dryer's Fan Before Action

Power Curve for the Chamber Dryer's After Action

The Future

The installation of meters is now being expanded to include three more dryers of different types. The goal is to understand how these dryers operate compared to each other, focusing on energy efficiency, power requirements, and the distribution between bioenergy and electricity.

Going forward, the team looks forward to integrating energy data with more systems. Using SenseNode's API, they connect the energy data with the dryer's control system, enabling real-time monitoring of energy use integrated into daily work.