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Supply chain glossary

Overall Equipment Effectiveness (OEE)

What OEE is, how availability, performance and quality multiply into one number and why the definition of planned time decides the result.

03. november 2026

2 min

Overall Equipment Effectiveness

Overall equipment effectiveness (OEE) is a metric that expresses how much of the planned production time a machine or line spends making good parts at its ideal speed. It multiplies three losses into one percentage: stops (availability), slow running (performance) and defects (quality).

The calculation uses three ratios:

  • Availability = run time / planned production time
  • Performance = (ideal cycle time × total count) / run time
  • Quality = good count / total count
  • OEE = availability × performance × quality = (good count × ideal cycle time) / planned production time

Because the ratios multiply, three moderate losses add up to a large one: 90% in each component gives an OEE of 73%.

OEE in practice

The result depends on what counts as planned production time. Take a line with 1,350 minutes of planned time per day after breaks, 120 minutes of unplanned stops and 90 minutes of changeovers. It runs 1,140 minutes, the ideal cycle time is 0.5 minutes, it produces 2,000 parts and 1,940 of them are good. Availability is 84.4%, performance 87.7%, quality 97% and OEE 71.9%. If the plant books changeovers as planned downtime, planned time falls to 1,260 minutes and OEE rises to 77.0%. The line made the same 1,940 good parts. Comparing OEE between plants or lines therefore only works with the same rules for planned time, and a benchmark figure without those rules says little.

The second limit is where the number is improved. Higher OEE on a machine that is not the bottleneck does not raise plant output, it only produces more work‑in‑process in front of the constraint. OEE pays off first on the constraint, where every minute of stops, slow running or scrap is a minute lost for the whole plant.

Logio uses OEE losses on the constraint as input for production capacity planning and tests with dynamic simulation which loss is worth removing first. Where availability is lost waiting for a spare part, the fix belongs to spare parts management, not to the line.

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