Key takeaways
Automatic downtime tracking captures every stop on a line, with its exact start, duration, and end, straight from the equipment signal or the production data. No one has to notice the stop or remember to write it down. That matters because the stops that hurt most are often the short, frequent ones that manual logging never records.
Tracking the stop is only half the job. A list of stops with no reasons tells you the line is losing time but not what to do about it. The value is in the second half: attaching an accurate cause to each one.
Most plants ask the operator to pick a reason code when a line stops. Under production pressure, with a queue building, the operator picks the nearest plausible code and moves on. Over a month, the data skews toward the easy categories and away from the truth.
The result is a downtime Pareto that looks authoritative and points in the wrong direction. Teams then spend improvement effort on a cause that was over-reported because it was easy to click, while the real driver hides inside a generic bucket. Accurate capture is what makes the analysis worth doing at all.
Confusing the two is common. A reliable immediate trigger is something a system can capture; the underlying cause is something a person investigates, far more easily when the trigger data is clean.
| Aspect | Manual reason codes | Automatic capture |
|---|---|---|
| Short stops | Rarely logged | Captured every time |
| Reason accuracy | Skewed to easy codes | Tied to the actual event |
| Recurrence visibility | Hidden in generic buckets | Visible across linked events |
| Improvement targeting | Often aimed at the wrong cause | Aimed at the real driver |
Fabrico tracks downtime automatically and uses computer vision to capture the true immediate cause of a stop instead of relying on an operator reason code, so your downtime data points where the problem really is. Because every event is linked and OEE and CMMS share one platform, recurring triggers are visible and a captured cause can become a work order directly. The underlying cause is still yours to investigate, but you start from clean data rather than guesses. Fabrico is built and hosted in the EU with data residency in mind and is ISO 27001 certified. To see it on your lines, book a demo.
For a practical next step, compare the leading options in our guide to the best production monitoring systems.
It reliably captures the immediate trigger (what stopped the line). The underlying cause, why that trigger keeps recurring, is still an investigation. The value of automatic capture is that the investigation starts from accurate data instead of skewed reason codes.
Under production pressure, operators pick the easiest plausible code, so the data drifts toward those categories. The downtime analysis then points at an over-reported cause while the real driver hides in a generic bucket.
Capture accuracy. Until the reason attached to each stop is trustworthy, every downstream chart and improvement plan is built on guesses. Reliable capture comes before any analysis.
Automatic tracking captures short, frequent stops that manual logging routinely misses, which is important because those small losses often add up to more than the dramatic breakdowns.
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