Illustrative scenario
A furnace over-cycling, seen on the air and gas traces together
Illustrative scenario — representative of common industrial IoT applications
Compressed airNatural gasMetal Fabrication & FinishingBuilding Materials & Heavy Industry
Short-cycling that neither the gas bill nor the air system showed alone.
A heat-treating operation
How it went.
Every study on this site runs the same four beats, in the same order.
01
Alert
A furnace was firing far more often than the process required. On a monthly gas bill it looked like ordinary seasonal variation.
02
Cost
2 utilities on one chart — The over-cycling pattern is only obvious when gas firing and air demand are overlaid.
03
Fix
Gas flow metering at the furnace · Compressed-air demand at the same asset · Firing-rate trending on one shared time axis
04
Restored
One overlaid trace where the cycling is unmistakable
In full.
Illustrative scenario — representative of common industrial IoT applications.
The problem
A furnace was firing far more often than the process required. On a monthly gas bill it looked like ordinary seasonal variation.
What would be installed
- Gas flow metering at the furnace
- Compressed-air demand at the same asset
- Firing-rate trending on one shared time axis
What changes
Before — Two utilities, two bills, no pattern After — One overlaid trace where the cycling is unmistakable
The number
2 utilities on one chart — The over-cycling pattern is only obvious when gas firing and air demand are overlaid. Illustrative scenario, not a client result. Figure is representative, not measured. [TOM-REVIEW]
In one line
Two traces on one axis is often the entire analysis.
What the data looked like.
Hover or arrow-key across the trace to read any interval. The flagged point is the one that started the conversation.
| Interval | Furnace 2 (m³/h) |
|---|---|
| 06:00 | 97 |
| 06:02 | 97 |
| 06:04 | 97 |
| 06:06 | 3.2 |
| 06:08 | 4.8 |
| 06:10 | 5.0 |
| 06:12 | 3.1 |
| 06:14 | 95 |
| 06:16 | 96 |
| 06:18 | 96 |
| 06:20 | 4.6 |
| 06:22 | 4.1 |
| 06:24 | 3.5 |
| 06:26 | 4.0 |
| 06:28 | 95 |
| 06:30 | 96 |
| 06:32 | 97 |
| 06:34 | 2.8 |
| 06:36 | 3.4 |
| 06:38 | 2.7 |
| 06:40 | 3.7 |
| 06:42 | 95 |
| 06:44 | 96 |
| 06:46 | 97 |
| 06:48 | 5.5 |
| 06:50 | 2.8 |
| 06:52 | 3.1 |
| 06:54 | 4.5 |
| 06:56 | 96 |
| 06:58 | 97 |
| 07:00 | 96 |
| 07:02 | 3.6 |
| 07:04 | 3.7 |
| 07:06 | 5.0 |
| 07:08 | 3.1 |
| 07:10 | 95 |
| 07:12 | 97 |
| 07:14 | 97 |
| 07:16 | 5.3 |
| 07:18 | 4.6 |
| 07:20 | 3.7 |
| 07:22 | 4.7 |
| 07:24 | 97 |
| 07:26 | 96 |
| 07:28 | 97 |
| 07:30 | 2.5 |
| 07:32 | 5.2 |
| 07:34 | 4.8 |
| 07:36 | 2.7 |
| 07:38 | 97 |
| 07:40 | 95 |
| 07:42 | 97 |
| 07:44 | 3.2 |
| 07:46 | 2.6 |
| 07:48 | 4.2 |
| 07:50 | 4.0 |
| 07:52 | 97 |
| 07:54 | 97 |
| 07:56 | 95 |
| 07:58 | 3.7 |
| 08:00 | 3.9 |
| 08:02 | 4.4 |
| 08:04 | 4.8 |
| 08:06 | 97 |
| 08:08 | 97 |
| 08:10 | 97 |
| 08:12 | 2.7 |
| 08:14 | 3.7 |
| 08:16 | 5.5 |
| 08:18 | 3.9 |
| 08:20 | 96 |
| 08:22 | 98 |
| 08:24 | 97 |
| 08:26 | 5.3 |
| 08:28 | 4.4 |
| 08:30 | 3.0 |
| 08:32 | 4.8 |
| 08:34 | 96 |
| 08:36 | 96 |
| 08:38 | 97 |
| 08:40 | 3.2 |
| 08:42 | 2.6 |
| 08:44 | 3.8 |
| 08:46 | 4.7 |
| 08:48 | 97 |
| 08:50 | 96 |
| 08:52 | 97 |
| 08:54 | 5.3 |
| 08:56 | 3.1 |
| 08:58 | 2.8 |
| 09:00 | 4.8 |
| 09:02 | 95 |
| 09:04 | 96 |
| 09:06 | 96 |
| 09:08 | 3.3 |
| 09:10 | 4.4 |
| 09:12 | 4.1 |
| 09:14 | 3.4 |
| 09:16 | 98 |
| 09:18 | 97 |
| 09:20 | 96 |
| 09:22 | 4.5 |
| 09:24 | 4.8 |
| 09:26 | 3.7 |
| 09:28 | 4.3 |
| 09:30 | 95 |
| 09:32 | 96 |
| 09:34 | 97 |
| 09:36 | 3.8 |
| 09:38 | 5.4 |
| 09:40 | 3.0 |
| 09:42 | 4.8 |
| 09:44 | 95 |
| 09:46 | 97 |
| 09:48 | 97 |
| 09:50 | 2.8 |
| 09:52 | 5.2 |
| 09:54 | 4.7 |
| 09:56 | 5.0 |
| 09:58 | 95 |
| 10:00 | 97 |
| 10:02 | 96 |
| 10:04 | 5.4 |
| 10:06 | 4.9 |
| 10:08 | 4.6 |
| 10:10 | 3.8 |
| 10:12 | 95 |
| 10:14 | 97 |
| 10:16 | 95 |
| 10:18 | 3.8 |
| 10:20 | 5.1 |
| 10:22 | 4.5 |
| 10:24 | 4.4 |
| 10:26 | 95 |
| 10:28 | 97 |
| 10:30 | 96 |
| 10:32 | 4.2 |
| 10:34 | 5.3 |
| 10:36 | 4.0 |
| 10:38 | 3.6 |
| 10:40 | 97 |
| 10:42 | 96 |
| 10:44 | 97 |
| 10:46 | 4.5 |
| 10:48 | 3.2 |
| 10:50 | 2.6 |
| 10:52 | 2.9 |
| 10:54 | 96 |
| 10:56 | 95 |
| 10:58 | 95 |
| 11:00 | 3.5 |
| 11:02 | 4.7 |
| 11:04 | 5.1 |
| 11:06 | 3.8 |
| 11:08 | 96 |
| 11:10 | 96 |
| 11:12 | 98 |
| 11:14 | 4.5 |
| 11:16 | 3.6 |
| 11:18 | 5.5 |
| 11:20 | 3.5 |
| 11:22 | 96 |
| 11:24 | 97 |
| 11:26 | 96 |
| 11:28 | 4.3 |
| 11:30 | 2.9 |
| 11:32 | 3.2 |
| 11:34 | 4.4 |
| 11:36 | 95 |
| 11:38 | 96 |
| 11:40 | 97 |
| 11:42 | 3.0 |
| 11:44 | 2.5 |
| 11:46 | 4.5 |
| 11:48 | 3.9 |
| 11:50 | 95 |
| 11:52 | 95 |
| 11:54 | 97 |
| 11:56 | 5.4 |
| 11:58 | 3.4 |
| Before | Two utilities, two bills, no pattern |
|---|---|
| After | One overlaid trace where the cycling is unmistakable |
Illustrative dataset — a representative operational profile, seeded and deterministic, not measured at any site.
What changed.
Before
Two utilities, two bills, no pattern
After
One overlaid trace where the cycling is unmistakable
2 utilities
on one chart
The over-cycling pattern is only obvious when gas firing and air demand are overlaid.
Source: Illustrative scenario, not a client result. Figure is representative, not measured. [TOM-REVIEW]
Where to go next.
The sector, the sibling studies, and the calculator that runs this same arithmetic on your own numbers.
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Illustrative scenario — representative of common industrial IoT applications
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Illustrative scenario — representative of common industrial IoT applications
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Illustrative scenario — representative of common industrial IoT applications
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