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Article · Data quality · 5 min read
The buffer illusion
Two lines can report the same interruption rate while one is healthy and the other is quietly falling apart. The difference is the stop threshold, a configuration choice that can turn a chronic problem into a clean-looking number. Here's how the illusion works, and the index that breaks it.
Published
In short
- Stop thresholds range from an aggressive 30s to a lenient 5 minutes.
- A lenient threshold lets operators clear faults before any stop reason is asked for.
- That moves faults out of the breakdown record: unplanned downtime looks lower, and those faults carry no reason.
- The Threshold Exposure Index (MTBI ÷ threshold × 100) exposes the illusion.
The same number, two very different lines
Put two lines side by side. Both report an interruption rate (interruptions are what standard OEE calls minor stops or micro-stops) in the low teens. One is genuinely stable. The other is stopping every fifteen seconds. Nothing in the headline number tells them apart, and that is exactly the problem. The variable doing the hiding is the stop threshold.
How the buffer masks the mess
A stop threshold is the delay before a pause is logged as downtime. Set it aggressively, at 30 seconds, and almost every stop shows up. Set it leniently, at 5 minutes, and a great deal moves out of the breakdown record: operators clear the fault and restart before the timer trips a stop reason.
The illusion in one line
One studied line reported a comfortable 12.86% interruption ratio, apparently optimised. Its real time between stops was 15 seconds. The generous 5-minute buffer let operators absorb a relentless stutter of faults invisibly, so the chronic faults, and the mechanical stress behind them, never reached the breakdown report with a cause.
The threshold moves time between buckets. Stops under it count as interruptions, without a reason, so the interruption share rises while unplanned downtime falls. Neither number shows how often the line stops. MTBI does.
The index that breaks it
To standardise across lines with wildly different thresholds, we use the Threshold Exposure Index, an index from our whitepaper, not an industry standard:
- TEI = MTBI ÷ stop threshold × 100
TEI is a research measure from our whitepaper. Ask us to work it out for your line.
It asks a simple question: how does a line's actual time between stops compare to the buffer it's allowed? The 12.86% line above scored a TEI of just 5.06%, stopping roughly twenty times faster than its threshold, a warning sign. A line with an aggressive threshold and long runs, by contrast, scores well above 100%, so its breakdown record is less likely to be masked. Any low TEI is a warning that the reported numbers are masked.
Clean data, real signal
The payoff of stripping the illusion is sharper analysis everywhere. Across the raw portfolio, MTBI and unplanned downtime correlated at a weak r = 0.41. Filter to the honest, high-TEI lines and the correlation jumps to r = 0.73. The buffer wasn't just hiding losses. It was hiding the relationships that explain them.
Check the TEI before you trust any downtime report. The buffer illusion is one of the core findings of the Interruption Whitepaper, and the reason MTBI should never be read on its own.
Questions
This article, answered
What is a stop threshold?
It's the delay a line waits before counting a pause as downtime. Below the threshold, a stop may be treated as an interruption or ignored; above it, the stop is logged with a stop reason. Thresholds in the study ranged from 30 seconds to 5 minutes.
How does a threshold create an illusion?
With a lenient 5-minute buffer, operators can clear a fault and restart before any stop reason is asked for. The fault is counted as an interruption, without a reason, so unplanned downtime looks artificially low.
What is the Threshold Exposure Index?
It is an index from our whitepaper, not an industry standard: TEI = MTBI ÷ stop threshold × 100. It normalises the time between stops against the configured buffer. A low TEI (well under 100%) means the line is stopping far faster than its threshold, so many of its faults may sit under the threshold, without a reason. Check the threshold before trusting its downtime report.
Why does this corrupt other metrics too?
Because masked breakdown data weakens every downstream analysis. In the study, filtering out low-TEI lines lifted the correlation between MTBI and unplanned downtime from r=0.41 to r=0.73. The noise was hiding the real signal.
Measure this on your own line.
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