INNOVATION
A US paper mill cut chemical waste by 18 percent with AI, showing how smart manufacturing can boost quality and sustainability
7 Feb 2025

A US board mill has reduced chemical waste by 18 per cent after introducing an artificial intelligence system that adjusts production chemicals in real time, in a shift that industry groups say could reshape efficiency and sustainability in paper manufacturing.
The system was developed through a partnership between specialty chemicals company Solenis and technology group ProcessMiner. It replaces traditional laboratory testing, which often involves delays between sampling and adjustment, with automated monitoring that changes chemical dosing as operating conditions shift.
Mill operators say the approach allows tighter control of production variables and helps maintain consistent product quality while lowering the amount of chemicals used.
The platform combines machine learning with sensors installed across the production process. These tools analyse operating data continuously and automatically adjust dosing levels, allowing mills to respond immediately to fluctuations in raw materials, temperature or machine performance.
Manufacturers in the pulp and paper sector are facing growing pressure to reduce emissions and improve resource efficiency while maintaining output. Industry executives say digital automation and predictive systems are becoming an important tool in meeting those targets.
“This kind of innovation shows how quickly we can move from sustainability talk to action,” said a senior Solenis executive. “We’re helping mills cut waste, meet emissions goals, and stay competitive, all without pausing production.”
The deployment also reflects broader efforts by suppliers to embed digital tools into traditional industrial processes. Solenis, which provides chemicals and process technologies to water-intensive industries, has expanded its focus on software and data-driven services in recent years.
Interest in similar systems is rising among North American paper producers, according to industry participants, particularly as demand grows for packaging linked to e-commerce and consumer goods.
Executives say future applications may include managing water and energy use more closely and predicting equipment failures before they disrupt production, though adoption across the sector remains at an early stage.
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