Illustrative scenario
Weekend ghost flow in an empty building
Illustrative scenario — representative of common industrial IoT applications
WaterFood & Beverage Processing
Water still running through an empty plant all weekend — around a fifth of the monthly bill.
A food processing plant
How it went.
Every study on this site runs the same four beats, in the same order.
01
Alert
The plant shuts down Friday evening and starts up Monday morning. The monthly bill never showed what happened in between, because a month is not a resolution.
02
Cost
~20% of the monthly water bill — Consumed with the building empty, over a weekend.
03
Fix
Flow meter on the incoming water service · Sub-meters on the two largest consumers · Overnight and weekend baseline alerting
04
Restored
A weekend baseline that should read zero, and an alert when it does not
In full.
Illustrative scenario — representative of common industrial IoT applications.
The problem
The plant shuts down Friday evening and starts up Monday morning. The monthly bill never showed what happened in between, because a month is not a resolution.
What would be installed
- Flow meter on the incoming water service
- Sub-meters on the two largest consumers
- Overnight and weekend baseline alerting
What changes
Before — A flat monthly number with no explanation inside it After — A weekend baseline that should read zero, and an alert when it does not
The number
~20% of the monthly water bill — Consumed with the building empty, over a weekend. Illustrative scenario, not a client result. Figure is representative, not measured. [TOM-REVIEW]
In one line
A weekend trace should fall to a flat line. When it does not, the gap between the line and zero is money leaving the building with nobody in it.
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 | Incoming service (L/min) |
|---|---|
| 00:00 | 46 |
| 00:30 | 47 |
| 01:00 | 46 |
| 01:30 | 45 |
| 02:00 | 47 |
| 02:30 | 46 |
| 03:00 | 45 |
| 03:30 | 46 |
| 04:00 | 46 |
| 04:30 | 47 |
| 05:00 | 46 |
| 05:30 | 47 |
| 06:00 | 46 |
| 06:30 | 47 |
| 07:00 | 46 |
| 07:30 | 47 |
| 08:00 | 46 |
| 08:30 | 46 |
| 09:00 | 47 |
| 09:30 | 46 |
| 10:00 | 44 |
| 10:30 | 46 |
| 11:00 | 45 |
| 11:30 | 46 |
| 12:00 | 45 |
| 12:30 | 47 |
| 13:00 | 47 |
| 13:30 | 46 |
| 14:00 | 46 |
| 14:30 | 47 |
| 15:00 | 45 |
| 15:30 | 47 |
| 16:00 | 45 |
| 16:30 | 47 |
| 17:00 | 45 |
| 17:30 | 44 |
| 18:00 | 45 |
| 18:30 | 47 |
| 19:00 | 46 |
| 19:30 | 45 |
| 20:00 | 47 |
| 20:30 | 44 |
| 21:00 | 45 |
| 21:30 | 47 |
| 22:00 | 47 |
| 22:30 | 46 |
| 23:00 | 45 |
| 23:30 | 46 |
| Before | A flat monthly number with no explanation inside it |
|---|---|
| After | A weekend baseline that should read zero, and an alert when it does not |
Illustrative dataset — a representative operational profile, seeded and deterministic, not measured at any site.
What changed.
Before
A flat monthly number with no explanation inside it
After
A weekend baseline that should read zero, and an alert when it does not
~20%
of the monthly water bill
Consumed with the building empty, over a weekend.
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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Blowdown running on a timer instead of on conductivity, discharging good water.
1 setpointchanged
Illustrative scenario — representative of common industrial IoT applications
Predictive maintenanceWaterBreweries & Beverage
A failing diaphragm pump, caught before it failed
Carlsberg Canada
A failing diaphragm pump caught before it failed — 540,000 L/day of loss prevented.
540,000 Lper day
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