AI-Based Low-Energy Strategic Systems for Enhanced (C)TMP Processes (ABLESS)

Research Project, 2025 – 2028

The aim is to control (C)TMP processes effectively. The goal is an energy efficiency improvement of 65 GWh/year (based on an annual production of approximately 550,000 tons) and a 25% reduction in variation in pulp properties to be achieved at a given heat balance and controlled process, through the use of advanced system-based AI models.

Expected effects and result
Significant energy efficiency can be achieved by using innovative control in the production of mechanical pulp (C)TMP. This project proposal includes the use and further development of advanced “soft sensors” based on physical modeling and advanced ANN - empirical models. Data from three reference mills will be used. The goal is to achieve at least 65 GWh savings annually while at the same time achieving a 25% reduction in the variation in pulp properties.