Energy
Run the same production on less energy by holding the process at its most efficient settings, not its safest ones.
Cut quality variability by up to 20%. Without adding headcount.
Quality variability isn't a lab problem, it's a timing problem. ProcessMiner predicts quality every 30 seconds and guides the correction before the quality deviation reaches the spec limit, so your current team holds tighter quality than a larger one could by reacting.
How quality gets made today vs. with ProcessMiner
Reactive quality vs. proactive quality
Today, quality is checked at the lab and the problem is discovered after the defect is already made. With ProcessMiner, quality is predicted every 30 seconds and the quality deviation is addressed before it reaches the spec limit. The line keeps running, in spec.
Reactive quality
Act after the outcome
Operators react only once off-spec product has already been made.
- Drift begins. The process quietly trends toward the spec limit, unseen between lab samples.
- Defect discovered at the lab. The result comes back after the batch is made; the loss is already booked.
- Late manual fix. The operator over-corrects, and variability widens on the next swing.
Proactive quality
Prevent before it happens
ProcessMiner predicts the trend and corrects in real time.
- Trend predicted every 30 seconds. The model predicts the quality deviation before it reaches spec.
- Correction recommended. Every 15 minutes, only when the trend is heading out of bounds.
- Defect prevented. Quality holds in target: no scrap, no rework, no extra headcount.
How the platform delivers this outcome
Three capabilities that improve quality together
Cutting variability by up to 20% isn't one feature. It's a loop: predict where quality is heading, find what's pushing it, and hold the process at its best-known settings.
01 / Real-Time Prediction
See the quality deviation before the lab does
Your lab tells you what already happened. The platform predicts quality every 30 seconds, per product grade/SKU, filling the blind spots between lab samples with a live trend your team can act on.
- Quality predictions every 30 seconds, continuously and live
- Grade/SKU-specific limits applied automatically across a wide range of grades/SKUs
- Recommendations every 15 minutes, only when action is needed
Reactive vs. proactive
02 / Root Cause Analysis
Know what's pushing quality, ranked by influence
When a quality prediction crosses a grade/SKU limit, the platform surfaces the top 10 to 15 process tags driving the quality deviation, ranked by influence. Your team fixes the cause instead of debating it, and variability stops repeating for the same reason.
- Triggered automatically the moment quality breaches its limits
- Top influencing tags ranked, from thousands of candidates per machine
- Cuts investigation from shifts of guesswork to a ranked short list
Ranked contributing factors
03 / Intelligent Centerlining
Hold every shift to your best run
The platform identifies your golden run, the settings that produced your best quality at the lowest cost, and keeps key process variables aligned to those targets in real time. Every crew, every shift, runs to the same proven centerline instead of personal preference.
- Golden-run targets derived from your own best production history
- Live radar-style dashboard shows drift from target at a glance
- Removes crew-to-crew quality variation, a major driver of quality spread
Centerline vs. current settings
Results from the field
What tighter quality is worth
These figures come from real ProcessMiner deployments in pulp and paper, not projections. Tighter quality shows up as less scrap, fewer giveaways, and margin that stays on the sheet.
>20%
Quality variability reduction
Pulp & paper deployments
63%
Better target adherence
vs. operator baseline
23%
Less quality variation
Tighter, consistent quality
$1.5M
Cumulative savings in 12 months
Single deployment
Figures reflect actual ProcessMiner deployments in pulp and paper. Results vary by facility, process, and data quality; past performance is not a guarantee of future results.
See it on your own process
Prove it on your data.
Bring six months of historical quality data. We'll show you where the variability is coming from, what a 20% reduction would be worth at your facility, and whether a pilot makes sense.
~30 min
to connect your historian
Hours
to a first live quality prediction model
Under 2 weeks
to full deployment
Get in touch
Have a question?
Whether it's our platform, your process, or a free in-depth process data analysis and pilot you'd like to see in action, let us know.