Integration of artificial intelligence and sustainable energy management in the pulp and paper industry: A path to decarbonization
Raine Viitala, Mikael Miettinen, Ronald Márquez, Aleksanteri Hämäläinen, Aku Karhinen, Nelson Barrios, Ronalds González, Lokendra Pal, Hasan Jameel, Kenneth Holmberg
Abstract
The pulp and paper industry (P&PI) faces significant energy challenges in advancing decarbonization efforts, particularly within its most energy-intensive processes, such as mechanical refining, dewatering and drying, and friction during papermaking. The objective of this review is to critically assess recent advances in energy management and artificial intelligence (AI) applications to enhance efficiency in papermaking processes. Following a systematic literature review based on PRISMA guidelines, the study examines the role of AI in optimizing mechanical refining, dewatering and drying, friction reduction , and condition monitoring. Results show that AI can fine-tune operational parameters in mechanical refining, leading to energy savings of up to 15 %. In dewatering and drying, AI-driven strategies improve heat recovery efficiency, potentially reducing energy consumption by 10–20 %. In friction management, AI-based optimization and the application of advanced technologies such as aerostatic bearings can reduce energy losses by up to 24 % in the long term. AI-driven condition monitoring strategies further reduce downtime and improve machine efficiency. The review concludes that AI offers considerable potential to improve energy efficiency and decarbonize the P&PI, but broader implementation is hindered by technological, financial, and organizational barriers.