Environmental impact of installed base management in mechanical pulp refining : A simulation-based approach with enzyme upgrade

Abstract

Mechanical pulp refining is the most energy intensive subprocess in chemi-thermomechanical pulp (CTMP) production line consuming up to 40% of total energy consumption of the whole CTMP mill. As global greenhouse gas (GHG) emissions are still growing in 2024 and the climate change is proceeding rapidly, greener solutions and approaches are needed also in the pulp and paper industries (PPI). The most efficient actions of machinery manufacturing industry come from companies willing to adjust and improve their ways of operating and to design new innovative climate-aware technologies. The improvement requires a coherent use and handling of product-related and installed base (IB) related data.

The value of IB data harvesting is studied in this thesis. Information is found from literature and a simulation-based approach to IB management. Effective management of IB data is crucial for tracking machinery performance, optimizing maintenance of machinery, and extending the lifecycle of equipment and machines. By refining the IB data and integrating it into IB management simulation tools, companies can identify opportunities to enhance customer’s energy efficiency and reduce the environmental impact of their equipment. Accurate data handling not only supports sustainability goals but also aids in developing predictive models for machinery operation. Economic and environmental savings can be obtained when leveraging comprehensive IB management in customer business.

In the context of environmental sustainability, mechanical pulp refining presents significant opportunities for reducing energy consumption and GHG emissions. The simulation conducted in this study demonstrated the impact of changing refiner segments and implementing energy-saving measures. Additionally, evaluating the recycling rate of refining segments and incorporating biotechnological innovations, such as enzyme applications, showed potential to optimize the refining process, decrease energy use, and minimize chemical consumption, contributing to a more sustainable CTMP refining process. Enzymes, such as xylanase, cellulase, and laccase can alter the wood matter or ready-made pulp so that it is easier to refine in mechanical refiners. In this thesis, a primary refiner was simulated, and it was found that for wood chips refining, laccase had the biggest impact. Biggest issues of enzyme technology arise from process conditions, where pH, temperature, retention time, and chemical environment are most critical. Enzymes require a longer retention time, but it also should be regulated to restrict overacting. All parameters should be studied before enzyme application to the refining process.

The IB management simulation was conducted in two parts where the first was done in Excel and the second in PowerBI. The results obtained showed cumulative energy reductions of 112–527 GWh, and cost reductions up to 16.1 M€ over the 10 years of inspection period. The results indicate huge savings both in energy and costs when efficient IB management is utilized. This requires harmonized data and efficient processes and systems for IB management. This study sets a base for further studies on the matter. The topic is wide and the addition of biotechnology to the topic gives it both perspective and diverseness. This study fills a gap of combined research of data science, environmental sustainability, and emerging biotechnological processes in the PPI.