Where a paper machine loses its year

Mills are among the best-instrumented plants in industry. The problem is almost never missing data — it is that the systems holding it never talk to each other.

What we connect to in your plant

Your DCS and QCS already hold most of this. We read across them, plus the drives, utilities and lab, and put them on a single timeline.

The signals we read, and what each one tells you

On a paper machine the useful unit is not the tag, it is the correlation — what the wet end was doing when the dryer section lost the sheet.

Signal What it tells you
Machine speed with break events tagged by section Cause attribution based on the seconds before the break, across every section, rather than on the shift log.
GSM, moisture, ash and caliper from the QCS scan Giveaway quantified in tonnes and currency, not just as a control chart that stays inside spec.
Refiner load and specific energy What fibre development is costing per tonne, and whether it is buying you any strength.
Stock consistency and freeness The upstream conditions that decide runnability two hours later.
Headbox pressure, vacuum levels and press loads Wet-end stability, which is where most break sequences actually begin.
Steam flow and pressure by dryer section Drying cost and profile, and the single biggest lever on cost per tonne after fibre.
Chemical dosing rates against production Consumption against standard by grade, which is where habitual overdosing shows up.
Broke and winder waste Yield loss traced to the reel and the conditions that produced it.
kWh and water per tonne Utilities cost per tonne by grade, shift and season.

The mill's numbers, on the same timeline

Production, quality, energy and maintenance stop reconciling four reports and start reading one.

Machine efficiency

%, by grade

Tonnes per day vs plan

tonnes

Breaks per day and MTBB

count and hours

Recovery time per break

minutes

GSM giveaway

% above target

Moisture variability

2σ

Specific energy

kWh per tonne

Steam ratio

tonnes steam per tonne paper

Water consumption

m³ per tonne

Chemical cost per tonne

currency

Grade change time

minutes and off-spec tonnes

Reel quality yield

% saleable

AI trained on your process. Not a generic factory.

Models built on continuous web processes, where the useful warning arrives in minutes and the cost of a false alarm is a slowdown, not a shutdown.

Break prediction

Learns the minutes-before signature across tension, consistency, vacuum and dryer profile, and warns the desk with enough lead time to slow down or intervene rather than lose the sheet and thirty minutes of production.

Giveaway optimiser

Shows how close to the lower spec limit the machine has genuinely run before, by grade and by crew, and holds the target there instead of at whatever margin feels comfortable.

Specific-energy benchmarking

Ranks shifts, grades and seasons on kWh and steam per tonne, then points at the setpoint combinations behind the best runs. On most machines this is the fastest payback available.

Grade-change playbook

Reconstructs the fastest historical path from grade A to grade B and gives the desk the sequence that produced the least off-spec, instead of leaving it to whoever is on shift.

Your first thirty days

One machine, read-only, with twelve months of history rebuilt in the first fortnight.

1

Connect one machine

DCS, QCS and sectional drives on a single paper machine, read-only. No changes to control, no interruption to production

 

2

Rebuild twelve months of history

Every break and every reel from the last year placed on one timeline. Break causes get ranked by evidence, often for the first time.

3

Add steam, power and water

Utilities join the timeline so a tonne can be costed properly by grade, shift and season.

4

Run live on one grade

Break watch and giveaway targeting go live for a single grade. The desk gets a number to hold and a warning worth acting on.

What plants aim for in the first quarter

10–25%

fewer sheet breaks on the connected machine

 

0.5–1.5%

GSM giveaway recovered against target

4–10%

reduction in specific energy per tonne

20–40%

faster grade changes with less off-spec

Target ranges for scoping a pilot. Replace with your own validated customer results before this page goes live.

Questions plant teams ask us first

We already have a QCS and a DCS with reporting. What does this add?
The value is in the joins, not in another trend screen. Your QCS knows the sheet, your DCS knows the process, the lab knows the reel and the meters know the energy — but none of them knows what the others knew at the moment the sheet broke. That correlation is the product.
Does it read or write to the control system?
Read-only. We do not sit in the control path and we do not change setpoints. Recommendations go to the desk, and the operator decides.
Our mill is old with equipment from four different vintages.
That is the normal case. Modern sections come in over OPC UA, older sections over Modbus or through retrofit instrumentation. Mixed vintage is a mapping exercise, not a blocker.
We run recycled fibre, so our furnish varies constantly.
Then the model is more valuable, not less. It retrains on your furnish and learns the relationship between incoming variability and runnability, which is precisely the thing crews currently absorb by running conservatively.
Can cogeneration be included?
Yes, and it should be. Steam and power balance is a large part of cost per tonne, and IEC 61850 relays and turbo-generator data come into the same timeline as the machine.