AI Pulp & Paper Mill Energy

AI for energy efficiency in pulping, papermaking, and drying processes

The Problem

“Cut mill energy costs amid process variability”

Organizations face these key challenges:

Unpredictable steam and power demand swings from grade changes, moisture variability, and equipment constraints leading to venting, letdown, or purchased power spikes

Hidden efficiency losses (fouling, steam trap failures, air leaks, poor combustion tuning) that accumulate for weeks before detection

Siloed decision-making between production, utilities, and maintenance causing suboptimal boiler/turbine dispatch and avoidable emissions/compliance risk

Impact When Solved

3–8% reduction in total energy spend via real-time steam/power optimization and price-aware dispatch2–6% fuel reduction and 2–5% CO2 intensity reduction by sustaining boiler efficiency and minimizing steam losses10–25% fewer energy-asset-related unplanned downtime hours through early anomaly detection and targeted maintenance

Real-World Use Cases

AI in Energy Industry: Smart Grid Optimization and Energy Management

This is like giving the entire power system—power plants, grids, and large customers—a real‑time ‘autopilot’ that constantly predicts demand, reroutes electricity, and tunes equipment so you use less fuel, waste less energy, and keep the lights on more reliably.

Time-SeriesEmerging Standard

8.5

AI for Optimizing Power Plant Operations

AI helps power plants run better and save money.

optimizationgrowing

7.0