The new system will be started up in November 2016. Valmet supplied a similar PQV system for the mill’s pulp drying line 4 in 2015.
The order was included in Valmet‘s third quarter 2016 orders received. Typically the order value of this kind of automation system deliveries is below EUR one million.
“The results reached with the traditional dirt count method on a light table and the PQV correlate well. Additionally, we now have access to real-time dirt count data in the control room without any delay, and this helps us to control our process faster and more precisely than before,” says Henrik Antila, Fiber Line Operations Manager, Stora Enso Sunila.
“This solution features excellent dirt count calculation thanks to its highly advanced defect analysis methods that allow constant, real-time detection of small dirt specks and shives on a fast moving web in the pulp drying processes,” says Jukka Paananen, Product Manager, On-Line Quality Management Solutions, Automation, Valmet.
Technical information about the delivery
Valmet’s PQV delivery to Stora Enso Sunila Mill features a Valmet IQ Web Inspection System (WIS) that consists of a high-definition matrix camera system and a matching light source to capture crystal clear images of defects in the sheet. Located on the pulp drying machine after the drying section, utilization of the PQV system gives the mill efficient and continuous online quality control.
Sunila’s operators can follow dirt count numbers on process control system displays in the control room. Also, they can check dirt distribution on a defect map that is available on a separate screen.
The PQV provides online proof of Sunila’s typically low dirt counts as dirt count quality control is based on measurements traceable to each bale table. Average dirt counts can be included in each customer delivery.
Unlike other web inspection systems, four matrix cameras allow the LED light beam to use an extremely short duration flash for sharp images unaffected by web speed. The camera system is flicker free and safe for human eyes, the short-duration flash requires little power and avoids heat buildup. Image analysis software with advanced detection algorithms detects and classifies even the smallest dirt specks and shives on the web.