Case Study: International Paper achieves real-time optimization, reduced waste, and improved product quality with Altair AI platform

Machine Learning Models Built in Altair AI Studio Display Real-time Data in Altair Panopticon Dashboards

International Paper, a global leader in renewable fiber-based packaging and pulp, needed to apply AI across its paper manufacturing processes to predict material composition (e.g., porosity), identify root causes of recovery-boiler fouling, enable predictive maintenance, and provide real-time operator guidance. To meet these challenges they partnered with Altair, deploying Altair AI Studio, Altair AI Hub and Altair Panopticon (part of the Altair RapidMiner platform).

Altair’s solution used AI Studio and AI Hub to build explainable predictive and prescriptive models, integrated with BrainCube and AVEVA PI for data ingestion, and Panopticon dashboards to display real-time KPI scores and recommended equipment settings. As a result, operators receive actionable, real-time recommendations; International Paper reports substantial reductions in energy and material waste, increased operational efficiency, and improved product consistency and quality using Altair’s tools.

International Paper

Andrew Jones

Senior Engineering Fellow, Data Scientist