Valmet reduces fiber costs with real-time strength control

Paper and board manufacturing, process automation, and quality management systems require continuous monitoring of product strength to ensure consistency while minimizing raw material consumption. In this context, Valmet has introduced the IQ Virtual Sensor, a software-based solution that provides real-time predictions of key strength properties using existing process data.

The system delivers minute-by-minute estimates of parameters such as tensile strength, tear resistance, burst strength, and short-span compression test (SCT), enabling operators to monitor product quality continuously instead of relying solely on delayed laboratory measurements.

Replacing delayed laboratory testing with continuous insight
In conventional paper production, strength properties are verified through laboratory analysis, which introduces time delays between production and quality feedback. To avoid off-spec batches, operators often apply safety margins by increasing fibre and starch usage.

The IQ Virtual Sensor addresses this limitation by generating continuous quality predictions during production. The system uses existing mill data and continuously learns from laboratory results to refine its models. This allows earlier detection of process deviations and supports corrective actions before defects occur.

By reducing uncertainty, mills can operate with tighter control limits while maintaining required product specifications.

Process optimisation and reduced resource consumption
Real-time visibility into strength properties enables operators to adjust process parameters more precisely. This reduces the need for conservative operating margins and lowers the consumption of fibre and starch, which are major cost factors in paper production.

The system also contributes to improved energy efficiency by stabilising production and reducing the frequency of corrective interventions. In addition, an integrated “what-if” simulation function allows operators to test process changes and evaluate predicted outcomes before applying them, supporting more informed and controlled decision-making.

Integration with existing quality control systems
The IQ Virtual Sensor operates locally within the mill environment, eliminating dependency on cloud infrastructure and ensuring fast response times and secure data handling. It integrates with Valmet DNA and Valmet DNAe automation systems, allowing predicted strength values to be visualised alongside other process and quality data.

As part of the Valmet IQ Quality Management Systems portfolio, the solution can also be combined with the Valmet IQ Quality Control System (QCS) to provide a unified view of quality parameters across the production line. This integration enables tighter control of critical variables and improved coordination between measurement and control functions.

Path toward closed-loop process control
While the IQ Virtual Sensor can be deployed as a standalone solution, it is designed to support further integration with advanced process control systems. When combined with Valmet Advanced Process Controls (APC), the system can enable closed-loop control strategies, where process adjustments are automatically applied based on predicted quality outcomes.

This approach supports higher process stability, improved product uniformity, and increased production efficiency, particularly in high-volume paper and board manufacturing environments.

Positioning within digital quality management solutions
Virtual sensing technologies are increasingly used in process industries to estimate parameters that are difficult or time-consuming to measure directly. Comparable approaches exist in advanced quality control platforms from suppliers such as ABB and Honeywell, which also use data-driven models for real-time process optimisation.

Key selection criteria include prediction accuracy, integration with existing control systems, response time, and the ability to reduce raw material consumption without compromising product quality. The IQ Virtual Sensor addresses these requirements by combining continuous learning, local data processing, and seamless integration into existing automation environments.

By replacing delayed laboratory feedback with real-time predictions, the solution enables paper and board producers to optimise strength control, reduce costs, and improve overall process efficiency.

Edited by Natania Lyngdoh, Induportals Editor — Adapted by AI.

www.valmet.com