Industries
Manufacturing — automotive, plastics & rubber
Compressed air, electrical demand and equipment health on factory floors where the oldest asset in the building is often the one that matters most.
Tier 1 and Tier 2 factories usually have excellent data about parts and almost none about the utilities that make them. Compressed air has no meter, demand charges disappear into an overhead line, and the presses that matter most are often the ones without a PLC. So we meter what is there, connect to what you already have, and leave your controls alone.
The compressed-air system is usually where the first month pays for itself. Air is the most expensive utility per unit of work in the building, it is almost never sub-metered, and a leak makes no noise anybody can hear over a stamping line. A Sunday leak-down test against a permanently installed flow meter turns “we probably have leaks” into a list of cells, in order, with a number beside each one.
Electrical demand is the second. A demand charge is set by a single fifteen-minute interval, which means a factory can pay all year for one afternoon when the dryer regen and the compressor happened to call together. You will never find that interval on a monthly bill, and you cannot miss it on a minute-by-minute trace. Once you can see it, you can usually schedule around it without buying anything.
Then there is the equipment itself. A bearing changes its signature weeks before it seizes, and the factories that get hurt worst are the ones running assets old enough that no vendor supports them any more. Those are exactly the assets we can put a sensor on: a vibration sensor on the housing, a current transformer clamped on the motor feed, a 4-20 mA transmitter tapped off whatever the machine already puts out. Nothing gets ripped out, nothing can write a command back, and no line has to stop while we install it.
Manufacturing — automotive, plastics & rubber
Photo slot · industry-manufacturing — pending the photography cull (§K.3 #27).
What we typically meter here.
We meter nine things across all our sites. These are the four to six that matter most in this sector, and each one links through to what it turned up in a real factory.
- 02
Electricity
Demand charges are often 30–40% of the bill.
See the peaks before the utility bills them. Shift, shave or schedule — the dashboard shows which pays.
- 04
Compressed Air
Leaks silently eat 20–30% of compressor output.
The most expensive utility per unit of work — and the easiest 20% you will ever recover.
- 06
Vibration
A bearing changes its signature weeks before it seizes.
The shift is invisible to the human senses and unmistakable in the trend.
- 07
Predictive Maintenance
Unplanned downtime runs $10,000+/hour at most factories.
The same repair, done on a Saturday instead of in a crisis. That difference is worth more than the part.
- 09
Process Monitoring
A hunch is not something you can act on. Data is.
Cycle counts, runtime, firing rate, product temperature — the process numbers your utility bill will never show you.
The money facts are §D.7’s and carry [TOM-REVIEW] before launch — §K.2 #15.
What the data looks like.
Representative operational data, not a client result — the shapes are real, the factory is not.
| Interval | Vibration RMS (mm/s) |
|---|---|
| 01 JUN | 2.01 |
| 02 JUN | 2.02 |
| 03 JUN | 2.00 |
| 04 JUN | 2.05 |
| 05 JUN | 2.08 |
| 06 JUN | 2.04 |
| 07 JUN | 2.05 |
| 08 JUN | 2.03 |
| 09 JUN | 2.08 |
| 10 JUN | 2.04 |
| 11 JUN | 2.12 |
| 12 JUN | 2.08 |
| 13 JUN | 2.07 |
| 14 JUN | 2.07 |
| 15 JUN | 2.07 |
| 16 JUN | 2.04 |
| 17 JUN | 2.09 |
| 18 JUN | 2.07 |
| 19 JUN | 2.07 |
| 20 JUN | 2.05 |
| 21 JUN | 2.06 |
| 22 JUN | 2.01 |
| 23 JUN | 2.03 |
| 24 JUN | 1.97 |
| 25 JUN | 2.03 |
| 26 JUN | 1.96 |
| 27 JUN | 1.97 |
| 28 JUN | 1.98 |
| 29 JUN | 1.95 |
| 30 JUN | 1.98 |
| 01 JUL | 1.96 |
| 02 JUL | 1.94 |
| 03 JUL | 1.93 |
| 04 JUL | 1.97 |
| 05 JUL | 1.96 |
| 06 JUL | 1.97 |
| 07 JUL | 1.98 |
| 08 JUL | 2.00 |
| 09 JUL | 1.96 |
| 10 JUL | 1.98 |
| 11 JUL | 2.00 |
| 12 JUL | 1.97 |
| 13 JUL | 2.03 |
| 14 JUL | 2.00 |
| 15 JUL | 2.01 |
| 16 JUL | 2.05 |
| 17 JUL | 2.10 |
| 18 JUL | 2.19 |
| 19 JUL | 2.33 |
| 20 JUL | 2.40 |
| 21 JUL | 2.51 |
| 22 JUL | 2.74 |
| 23 JUL | 2.90 |
| 24 JUL | 3.06 |
| 25 JUL | 3.34 |
| 26 JUL | 3.56 |
| 27 JUL | 3.85 |
| 28 JUL | 4.10 |
| 29 JUL | 4.46 |
| 30 JUL | 4.73 |
Representative sets are flagged provenance: representative in src/data/widgets/ and are hot-swappable for the real sets (G6) with no markup change — §K.3 #28.
What it found in factories like yours.
Illustrative scenario
water
Chiller circuit leak isolated without a shutdown
An automotive factory
A leaking cooling loop found and isolated with the line still running.
Illustrative scenario
compressed-air
Compressed air leaks in a stamping operation
A Tier 2 automotive stamping factory
The most expensive utility per unit of work, leaking into an empty building overnight.
Illustrative scenario
predictive-maintenance
Conveyor drive bearing degradation caught six weeks early
A bulk handling facility
A bearing changed its signature about six weeks before it would have seized.
Illustrative scenario
cooling-towers · water
Cooling tower blowdown optimization
A plastics manufacturing factory
Blowdown running on a timer instead of on conductivity, discharging good water.
All 7 case studies in this sector
A study marked Illustrative scenario is representative of common industrial IoT applications: no client is named, no logo is shown and no figure on it was measured at any site. G4 — every industry slug must resolve to at least two case studies; the build gate asserts it (J.9.4).
Book a site walk.
Half a day on your floor, no charge and no obligation. At the end of it we tell you what we saw, what we would meter first, and what the return looks like.
or call 1-833-QUANTFY (1-833-782-6839)
