Pulp and Paper Mill Energy

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

The Problem

“Reduce steam, electricity, and thermal energy waste across pulp, paper, and drying operations”

Organizations face these key challenges:

1

High steam usage in dryer sections due to suboptimal moisture and condensate control

2

Energy-intensive refining and stock preparation with variable fiber characteristics

3

Poor coordination between production targets and utility system constraints

4

Frequent process variability causing over-drying, rework, and quality losses

5

Limited visibility into real-time specific energy consumption by grade and machine

6

Manual root-cause analysis for boiler, turbine, and steam network inefficiencies

7

Difficulty simulating rare but high-impact emergency or utility failure scenarios

8

Siloed OT data across DCS, PLC, historian, MES, and maintenance systems

Impact When Solved

3% to 10% reduction in steam consumption per ton of paper2% to 8% reduction in electricity consumption across pumps, fans, refiners, and vacuum systems1% to 5% increase in paper machine throughput through better drying and moisture control10% to 30% faster detection of energy losses and abnormal operating conditionsReduced CO2 emissions through lower fuel use in boilers and thermal systemsImproved operator decision speed during process disturbances and utility constraints

The Shift

Before AI~85% Manual

Human Does

  • •Review energy KPIs, audit findings, and recent utility trends across boilers, turbines, evaporators, and paper machines
  • •Adjust steam, power, and fuel setpoints manually based on operator experience, production plans, and current constraints
  • •Coordinate production, utilities, and maintenance priorities during grade changes, demand swings, and off-spec events
  • •Investigate visible efficiency losses and schedule corrective actions after performance degradation is observed

Automation

  • •Display static dashboards and historical trend summaries
  • •Apply fixed control rules and alarm thresholds in existing operations
  • •Produce basic spreadsheet-based steam and power balance calculations
With AI~75% Automated

Human Does

  • •Approve or reject recommended dispatch, setpoint, and load-balancing actions within safety, emissions, and production priorities
  • •Handle exceptions during abnormal equipment behavior, quality risks, or conflicting operating objectives
  • •Prioritize maintenance and operational interventions based on AI-flagged efficiency losses and root-cause insights

AI Handles

  • •Forecast mill-wide steam, power, and fuel demand from production conditions, asset state, and external factors
  • •Continuously optimize boiler, turbine, evaporator, and paper machine operating targets to minimize total energy cost
  • •Detect early efficiency drift, steam losses, and abnormal energy behavior and triage likely causes
  • •Generate real-time recommendations for dispatch, setpoint changes, and price-aware energy balancing across interacting systems

Operating Intelligence

How it works

AI runs the first three steps autonomously.

Humans own every decision.

The system gets smarter each cycle.

Confidence93%
ArchetypeRecommend & Decide
Shape6-step converge
Human gates1
Autonomy
67%AI controls 4 of 6 steps

Who is in control at each step

Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.

Loop shapeconverge

Step 1

Assemble Context

Step 2

Analyze

Step 3

Recommend

Step 4

Human Decision

Step 5

Execute

Step 6

Feedback

AI lead

Autonomous execution

1AI
2AI
3AI
5AI
gate

Human lead

Approval, override, feedback

4Human
6↺ Loop
AI-led step
Human-controlled step
Feedback loop
TL;DR

AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.

The Loop

6 steps

1 operating angles mapped

Operational Depth

Technologies

Technologies commonly used in Pulp and Paper Mill Energy implementations:

Data analytics toolsOther
4 mentions
AI algorithmsOther
3 mentions
Simulation softwareOther
3 mentions
Digital twinsOther
2 mentions
Scenario simulation engineOther
2 mentions

Key Players

Companies actively working on Pulp and Paper Mill Energy solutions:

GEHoneywell

Real-World Use Cases

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