What is OEE?
OEE — Overall Equipment Effectiveness — answers a deceptively simple question: of the time this machine was scheduled to produce, how much of it made good parts at full speed? It is a single percentage built from three factors:
OEE = Availability × Performance × Quality
Availability is run time divided by planned production time. It falls every time the line stops — breakdowns, changeovers, waiting on material. Performance compares the count you actually made while running against the count the machine’s ideal cycle time says you should have made; it falls to slow cycles and brief, unrecorded micro-stops. Quality is good parts divided by total parts; it falls to scrap and rework.
Multiplying the three matters. A line can look busy all shift (high availability) while crawling (poor performance), or run fast while making scrap. OEE refuses to let any one factor hide behind the others — which is why a genuinely good shift is rarer than it feels, and why most first OEE measurements surprise the people who take them.
Downtime tracking
Ask a plant where its time goes and you will usually get a clipboard: operators writing down stops from memory at the end of the shift, in round numbers, with the embarrassing reasons left vague. The data isn’t dishonest — it’s just human. Studies of manual logging routinely find a large share of stop time never recorded at all, and short stops almost never.
Automatic detection fixes the timing problem: the stopwatch starts when the machine stops and ends when it restarts, whether anyone writes anything down or not. The operator’s only job is the part a sensor can’t do — naming the reason. A short list of reason codes (changeover, material wait, tool change, breakdown, no operator) tapped at restart turns raw stop time into a Pareto you can act on.
Two habits make downtime data trustworthy: keep the reason list short enough to tap in seconds, and treat uncoded stops as a metric in themselves. When uncoded time creeps up, the measurement system — not the operator — is what needs attention.
The Six Big Losses
The Six Big Losses are the classic breakdown of where productive time goes. Each one maps cleanly onto an OEE factor:
- Availability losses: (1) equipment failure and breakdowns, (2) setup and changeover — the time between the last good part of one job and the first good part of the next.
- Performance losses: (3) idling and minor stops — jams, misfeeds, and sensor trips too short to log by hand, (4) reduced speed — running below ideal cycle time because of wear, settings, or caution.
- Quality losses: (5) process defects — scrap and rework made while running, (6) startup and yield losses — the bad parts made while a process warms up or settles after a changeover.
The framework’s value is discipline: when a shift’s OEE drops, you can walk the six losses in order and find which one moved, instead of debating impressions. Most plants discover the same surprise — the losses that feel biggest (breakdowns) are often smaller than the quiet ones (minor stops, slow running, long changeovers) that nobody was measuring.
OEE benchmarks & the 85% question
The most quoted number in manufacturing is 85% OEE — “world class.” It comes from multiplying three demanding targets: 90% availability × 95% performance × 99.9% quality = 85.4%. It was a stretch goal for the best-run discrete manufacturing lines, and it assumes those plants define their planned time and ideal rates the same way you do.
A commonly cited range for a typical plant is 40–60% OEE on first honest measurement — which shocks teams who expected 80%. The gap is usually not laziness; it is the unmeasured losses (minor stops, slow cycles, uncoded downtime) becoming visible for the first time.
Use benchmarks carefully. OEE is only comparable when the definitions match: what counts as planned time, whose ideal cycle time, whether changeovers are inside or outside the number. The most useful benchmark is your own line last month. A plant that moves from 52% to 61% OEE has added the equivalent of a free shift of capacity every week or so — whatever the world-class posters say.