Every point of lost overall equipment effectiveness traces back to one of six categories of waste. The Six Big Losses are the shared language that turns a vague OEE number into a list of specific, fixable problems. This guide maps each loss to its OEE factor, the data signal that reveals it and the countermeasure that removes it, so a production manager can move from a score to an action plan.
Three OEE factors, six losses, one language
Overall equipment effectiveness multiplies three factors: availability, performance and quality. Each factor is eroded by two of the six big losses OEE framework, giving the six categories that explain where capacity goes. The value of the framework is that it is exhaustive and shared. Calculated in line with ISO 22400-2, the same loss buckets mean the same thing across lines, shifts and sites, so improvement conversations stop being about opinions and start being about data.
The median plant runs at about 60 percent OEE, the top quartile at 75 and world-class operations at 85, while the discrete-manufacturing average sits near 66. The gap between your line and world-class is not a mystery. It is the sum of these six losses, and most of it lives in the hidden factory of 30 to 45 percent capacity that never shows up on a daily report drawn from manual logs.
How the losses map to the factors
- Availability losses: unplanned breakdowns and setup or changeover time.
- Performance losses: minor stops and idling, and running below rated speed.
- Quality losses: startup and warm-up rejects, and in-process production defects.
- Together they account for the full gap between rated capacity and good output.
The full Six Big Losses table
The table below is the working core of the framework. Each of the six losses is tied to the OEE factor it degrades, the data signal that exposes it and the countermeasure that addresses it. Read it as a diagnostic: find the loss with the largest signal on your line, apply the matching countermeasure, then re-measure. The point is to attack the biggest loss first, not to spread effort evenly.
Manual logs cannot drive this table. They overstate OEE by 8 to 15 points precisely because they miss minor stops and round breakdowns, so the signals you most need to act on are the ones paper hides. Automatic capture at the machine, with reason codes, is what makes each row actionable in real conditions.
| Loss category | OEE factor | Data signal | Countermeasure |
|---|---|---|---|
| Breakdowns | Availability | Long unplanned stops, falling MTBF | Root-cause analysis, preventive and condition-based maintenance |
| Setup and adjustment | Availability | Recurring changeover stops, long first-good time | SMED, internal to external conversion, presets |
| Minor stops and idling | Performance | Frequent short stops under a threshold | Capture micro-stops, fix feeds, jams and sensors |
| Reduced speed | Performance | Cycle time above the ideal rate | Restore rated speed, tune parameters, train operators |
| Startup rejects | Quality | Scrap clustered at job start and warm-up | Standardize startup, stabilize first-good settings |
| Production defects | Quality | In-run scrap and rework rate | In-process checks, QualTrak control, mistake-proofing |
At Hutchinson, a Tier-1 automotive supplier across 40 sites in 12 countries, real-time OEE monitoring accompanied an improvement from 42 to 75 percent, a gain of 33 points.
See your six losses ranked, not estimated
Run a free 60-day pilot on one line and let automatic capture rank your six big losses by real lost time within about two weeks.
Download the Six Big Losses guide
The full loss-to-countermeasure table, the data-signal map and the ISO 22400-2 method. We send it to your work email.
The data signal is the missing half of the framework
Most teams know the six losses by name yet still cannot say which one costs them the most, because they lack the signal. A breakdown shows up as a long unplanned stop and a falling MTBF. Minor stops show up as a swarm of short stops under a threshold that no operator logs. Reduced speed shows up as cycle time drifting above the ideal rate. Each loss has a fingerprint in the data, and you cannot remove what you cannot see.
PerfTrak captures these signals automatically at the machine, and the TeepTrak Box reads even legacy assets at the edge with no PLC. With every stop reason-coded and every cycle timed, the six losses sort themselves into a Pareto, and the largest loss declares itself instead of being guessed at in a meeting.
From the table to a ranked action plan
Eliminating the Six Big Losses is not a campaign, it is a loop. Measure the losses, rank them, apply the matching countermeasure to the biggest, then re-measure and move to the next. Because the categories are exhaustive, you never run out of structured targets, and because they map cleanly to availability, performance and quality, every fix shows up in the OEE number it was meant to move.
Run this loop with real data and the trajectory is predictable. The same discipline took Hutchinson from 42 to 75 percent OEE across a large automotive footprint, closing most of the gap to world-class. The first losses usually surface within about two weeks of measuring, and a well-scoped project typically pays back in 3 to 12 months.
- Map each of the six losses to its OEE factor before you act.
- Use the data signal to rank losses by real lost time, not opinion.
- Apply the matching countermeasure to the biggest loss first.
- Re-measure and loop, because the six categories are exhaustive.
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