Abstract
The pulp and paper industry has significant potential to reduce its carbon footprint by optimizing energy and water usage, contributing to global efforts toward net-zero emissions. A critical unit operation in this industry is pulp washing using twin roll press washers, which enhance pulp quality. The filtrate from this unit operation can be concentrated and combusted to generate a significant amount of energy for the plant and nearby industries. However, these washers are prone to blockages that disrupt production and decrease energy efficiency. Despite their importance, models for managing blockages in twin roll press washers are lacking. This study addresses this gap by developing empirical models to predict roll speed based on key process parameters. These models performed well on a case study of un-sanitized data from a real pulp and paper plant, achieving R2 of the order of 0.7. The models can potentially be used by operators to ensure uninterrupted production, and optimize resource usage, supporting the industry’s sustainability and decarbonization goals.