Large loads. Large bills. The same method.
Zebblo's method is not specific to refrigeration. It learns what normal looks like from the data your site already records, and flags the deviations that cost energy, oil and production time.
Zebblo fits industrial sites like these.
If most of these describe your site, the same engine we use in cold chain applies to you.
- Energy is one of your three largest operating costs.
- Your site already records data: energy meters, SCADA, a BMS or a process historian.
- Large motors, pumps, fans, compressed air, hydraulics or process heat drive your bill.
- An unplanned stop costs you more than the energy itself.
- You want proof that a change worked, not just a dashboard.
Where industrial sites lose energy and time.
Equipment that runs idle.
Or runs harder than the process needs.
Leaks and high pressure.
Pressure set higher than needed, and leaks that run around the clock.
Oil use rising faster than normal.
Caught before an alarm or a trip.
Heat that does not match output.
Heat use compared with output, line by line.
Peaks at shift start.
Load in expensive hours, peaks at shift start, and power-factor penalties.
Predictive hydraulic leak detection for a cold rolling mill
We defined an AI use case with the engineering team of an aluminium cold rolling mill. The mill's hydraulic system holds roll-gap force during rolling. A slow leak wastes costly oil, creates a safety hazard and can end in a protection trip that stops the mill. Today, such leaks are often found by hand, after a second low-level alarm.
Zebblo's approach learns normal oil consumption for each operating condition, using data the mill already records. It flags a developing leak as a deviation, hours before the physical alarm, without the false alarms a fixed threshold produces. The method is proven first on historical data, before anything goes live.
One use case. Proven on your own history.
Choose one problem.
We choose one problem with your team: a cost, a failure mode or a recurring alarm.
Test on your history.
We test Zebblo on your historical data and show what it would have caught, and when.
See it before it goes live.
You see the result before anything goes live, and decide whether to continue.
Built on the data your site already records.
- Optimize uses data from your meters, SCADA and historians. You do not need new hardware.
- Zebblo learns normal behaviour for each operating condition, so it raises fewer false alarms than a fixed threshold.
- Each finding comes with its likely cause and its cost.
- Savings are verified and corrected for production volume.
- Audit & Report supports ISO 50001, the German Energy Efficiency Act and energy audits, and the Carbon Credit Trading Scheme in India.
See where you could save on energy.
or write to us at abhishek@zebblo.com to discuss your specific needs.
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