The filler was starving, not failing
A bottling and packing plant blamed its filler for lost time. The data told a different story: two lines drew from one shared tank, and the filler kept starving while the downstream boxing machine ran on. The bottleneck was supply timing, not the machine.
- The filler was blamed for repeated stops and lost output.
- The data showed it was starving for supply, not breaking down.
- Two lines shared one tank, and the timing was out of sync.
- The supply mismatch accounted for more than 30 lost hours a month.
Your plant, the same method. One sensor per line, live within 48 hours of the kit arriving.
Blaming the wrong machine
The plant had a prime suspect. The filler stopped repeatedly, output suffered, and the maintenance conversation had settled on the machine itself: it was old, it was temperamental, it needed replacing. Every stop reinforced the story. What no one could explain was why a machine that stopped so often ran perfectly well the moment it did run.
Following the stops upstream
Augos monitored the line and looked at when the filler's stops actually happened. They did not correlate with any mechanical fault on the filler. They correlated with the level in the shared supply tank that fed two packing lines at once. When the tank ran low, the filler starved and stopped. When it was full, the filler ran cleanly. The machine wasn't failing, it was waiting.
Two lines drew from one tank, and their timing wasn't synchronised. The downstream boxing machine kept pulling product while the tank was low, so the filler and its own supply were effectively competing for the same liquid.
Fixing timing, not the filler
Once the cause was supply synchronisation rather than a failing machine, the fix moved off the maintenance budget entirely. The fix the data pointed to was coordinating the two lines' draw on the shared tank, so the filler stays fed. The mismatch had been costing the plant more than 30 hours of run-time a month, a loss no new filler would have touched.
The lesson repeats across plants: a machine that stops a lot is not always a broken machine. Sometimes it is a starved one, and only data that follows the problem upstream will tell you which.
More results like this.
What monitoring reveals when you leave it running
One line, watched continuously for four months. Planned downtime took a third of its time, and the trend kept surfacing slow drifts a one-off audit would miss.
Read the case study → Food and beverage · Beverage bottlerThe filler was not the problem
A beverage bottler blamed its filler for a line that kept stopping. The first month of monitoring showed 9,848 stops, nearly a quarter of paid time spent waiting, and an air-supply loss of over 34 hours.
Read the case study → Packaging and bags · Bag manufacturerThree shifts, one live board
A three-shift bag maker tracked output on paper, one number per shift. Demand was rising and nobody could say whether the machines had headroom. A live record of every stop answered it with data.
Read the case study →How did the data show it was starving, not failing?
The filler's stops lined up with an empty or low shared tank, not with any fault on the machine itself. When supply was available the filler ran cleanly; the stops tracked the tank, not the equipment.
Why did the boxing machine make it worse?
The downstream boxing machine kept drawing product while the tank was low, so the filler and its supply were competing. Synchronising the two lines' draw is the fix the data pointed to.
How much time was at stake?
The supply-timing mismatch accounted for more than 30 hours of lost run-time a month, none of it caused by the filler that had been blamed for it.
Find losses like these on your own line.
A 30-minute call with a manufacturing specialist. We look at one of your lines together and show you what the first week of data would say about it.
- Live within 48 hours of your kit arriving
- One sensor, one terminal, no PLC and nothing to integrate
- R4,950 per line per month, ex VAT. 90 days, then a month's notice