Death by a thousand interruptions
A packing site had an OEE of 26.5% and no obvious villain. There was no big breakdown to point at. The losses were 218,000 tiny stops, each too short to notice, all dumped into a single uncategorised bucket that hid the real story.
- OEE of 26.5% with no single breakdown to blame.
- The losses were 218,000 interruptions over the measured period.
- All of them were collapsed into one uncategorised downtime bucket.
- Finer data resolution made each stop cause visible and fixable.
Your plant, the same method. One sensor per line, live within 48 hours of the kit arriving.
A bad number with no explanation
The line's OEE sat at 26.5%, low enough to be alarming, and yet there was no obvious cause. The maintenance log was quiet. There had been no major breakdown, no long outage, nothing dramatic enough to explain why the line was producing at barely a quarter of its potential. By every account the line was "running fine". It simply wasn't producing.
When a line is losing that much time with nothing to point at, the losses are almost always small and frequent rather than large and rare. The problem is that the tracking in place could not see small and frequent.
Turning up the resolution
Augos captured the line's stops at a much finer resolution than the site's existing system. The result was stark: over the measured period the line had suffered 218,000 individual interruptions, short halts of seconds at a time (what standard OEE calls minor stops or micro-stops), each one previously invisible because it was too brief for the old tracking to register. Every one of them had been swept into a single uncategorised downtime bucket.
218,000 stops collapsed into one line item looks like an unsolvable mess. Split out by cause, it becomes a short list of specific, fixable problems, each responsible for tens of thousands of the stops.
From a mess to a to-do list
Categorising the interruptions did the real work. Instead of 218,000 problems there were a handful of root causes, a feed that jammed, a sensor that tripped, a station that choked, each accountable for a huge share of the total. That turned an intimidating, formless loss into an ordinary engineering backlog: fix the top cause and stops disappear in their tens of thousands.
The wider point is about measurement, not machinery. A line can be quietly losing three-quarters of its capacity to stops no one is recording. If the data can't see a two-second halt, it can't see the biggest loss on the floor, and the OEE number stays a mystery.
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 →What is an interruption?
A very short stoppage, often seconds, where the line halts and restarts. Individually they are trivial; at scale they can be the single largest loss on a line, and coarse tracking never records them.
Why did they all land in one bucket?
The existing tracking recorded downtime at a resolution too coarse to see short stops, so anything that didn't fit a named category was swept into a single 'other' or uncategorised total.
How do you fix 218,000 stops?
You don't fix them one by one. Once they are categorised you find the handful of causes behind the vast majority, and fixing those causes removes stops in their thousands.
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