The challenges and benefits of autonomous chemistry optimization

What it really takes to move from operator-led dosing to closed-loop chemistry control in a paper mill — and the payoff.

Using AI to speed up paper production and lower costs

Where machine learning creates throughput and cost headroom on the paper machine — without new capital equipment.

The future of pulp & paper manufacturing

Where the industry is heading as AI, autonomy, and sustainability pressure reshape the mill floor.

A rare-event dataset from a pulp-and-paper process (Part 1)

The multivariate time-series dataset behind the rare-event series — widely referenced across the ML community.

Rare-event classification in multivariate time series (Part 2)

Modeling approaches for extreme class imbalance, applied to a rare-event downtime dataset.

Board mill lowers chemistry dosage 18%

Continuous quality prediction and centerlining trimmed additive dosage 18% without sacrificing sheet strength.

Board mill optimizes Kymene consumption 25%

Targeted wet-strength resin control reduced Kymene use 25% while keeping quality inside spec.

Board producer reduces chemistry consumption 14%

A 14% reduction in chemical spend, achieved by acting on predicted quality rather than lab lag.

First autonomous chemistry control on a tissue machine

A milestone deployment: closed-loop chemistry control running live on a tissue line — the origin of ProcessMiner's physical-AI approach.

How a paper mill saved $600K a year in chemistry costs

Real-time quality prediction and autonomous chemistry control let one mill trim additive dosage while holding spec — six figures of recurring savings, no capital project required.