Moving from Descriptive to Prescriptive Analytics Using AI: Success Stories in Papermaking, TAPPICon24

A new approach to modernizing papermaking operations is available by using artificial intelligence (AI) and predictive analytics to provide real-time measurements and feedback to optimize production quality and efficiency. Unlike traditional papermaking operations that rely on laboratory tests conducted over time OR periodically, this approach uses machine learning algorithms that provide instant feedback on key process indicators. Instantaneous feedback allows operators to make informed control decisions and appropriate and timely adjustments to improve efficiency and reduce off-quality production.

This paper discusses how AI can be used in papermaking operations, how it can be used to inform control decisions, and what its potential benefits are. Specifically, the team will discuss how AI enables predictive analytics by providing real-time understanding of indicators such as speed changes, kappa swings, and chemistry changes. The authors also explore the potential use of AI for utilizing existing data from laboratory tests to further refine predictive accuracy. Finally, the team presents an example case study from a large paper mill that implemented this approach and discuss their results, including efficiency gains and quality optimization.

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