OEE calculator — availability, performance and quality
Calculate OEE from planned time, downtime, ideal cycle time and unit counts. Availability, performance and quality shown separately, plus TEEP.
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Short answer
OEE is availability × performance × quality. Availability is run time ÷ planned production time, performance is (ideal cycle time × total count) ÷ run time, and quality is good count ÷ total count. With 793 run minutes out of 840 planned, 1,412 units at a 30-second ideal cycle and 1,380 good, OEE is 82.1%.
OEE answers one question: of the units this asset could have made in the time you gave it, how many good ones did you actually get? A single percentage hides that, which is why this OEE calculator reports availability, performance and quality separately before multiplying them.
Enter planned production time, unplanned downtime, your ideal cycle time and the total and good counts. You get all three factors, OEE, TEEP against calendar time, and the lost units split across the three loss types so you know which one to work on Monday.
Your numbers
min
Time the asset was scheduled to run. Take out planned maintenance, unstaffed shifts and no-demand time first.
min
Every unplanned stop inside planned time: breakdowns, changeovers, material starvation, jams.
Enter the ideal rate as
s / unit
The fastest cycle this asset has sustained for this part. Not the routing standard — that includes allowances and will push performance above 100%.
units
Everything produced during run time, good and bad together.
units
Passed first time. Reworked units are not good units — count them as losses or quality disappears from the maths.
min
All time, for TEEP: 1,440 minutes a day, 10,080 a week. Shows what the asset could do if you scheduled it fully.
Result
Overall equipment effectiveness
82.1%
1,380 good units of the 1,680 possible in 840 planned minutes
Availability94.4%
Performance89.0%
Quality97.7%
OEE82.1%
Run time793 of 840 min
Ideal cycle / rate30.0 s = 120 units/hr
Units lost to all causes300 units
Utilisation (planned ÷ calendar)58.3%
TEEP (OEE × utilisation)47.9%
OEE restated in units, which is the version a shift meeting argues about.
82.1% is a normal, workable OEE. The biggest loss is 174 units, so attack performance — micro-stops and reduced running speed first.
Everything is computed in your browser. Nothing you type is sent anywhere or stored.
The formula
OEE = Availability × Performance × Quality, where Availability = Run time ÷ Planned production time, Performance = (Ideal cycle time × Total count) ÷ Run time, Quality = Good count ÷ Total count
Planned production time
Time the asset was scheduled to make product. Planned maintenance, unstaffed shifts and no-demand time are excluded before you start.
Run time
Planned production time minus every unplanned stop, including short stops the operator never logged.
Ideal cycle time
The fastest sustained cycle the asset has ever achieved for this part, not the standard on the routing.
Total count
Every unit the asset produced during run time, good and bad together.
Good count
Units that passed first time. Reworked units are not good units.
OEE = (Ideal cycle time × Good count) ÷ Planned production time gives exactly the same number in one step. Use the three-factor version anyway — the single figure tells you nothing about which loss to attack. TEEP replaces planned production time with all calendar time, so it measures the asset against the 168-hour week.
Run time is 840 − 47 = 793 minutes, so availability is 793 ÷ 840 = 94.4%. At 30 seconds a unit, 1,412 pieces should have taken 42,360 seconds against 47,580 seconds of run time, so performance is 89.0%. Quality is 1,380 ÷ 1,412 = 97.7%. Multiply the three and OEE is 82.1%. The same shift could have made 1,680 good units, so 300 units went missing: 94 to downtime, 174 to slow running, 32 to scrap. Performance is the biggest single loss, which is where the improvement money is.
How this OEE calculator splits the losses
Every OEE point you lose belongs to exactly one of three buckets, and the fix for each is completely different. Convert the percentages back into units before you take them to a meeting — nobody argues with "we left 300 pieces on the floor".
Factor
What it measures
Typical cause
Where the fix lives
Availability
Stops that took the asset out of production
Breakdowns, changeovers, material starvation
Maintenance, setup reduction, upstream supply
Performance
Running slower than the ideal cycle
Micro-stops, worn tooling, reduced feed rates, operator pace
Standard work, tooling condition, jam removal
Quality
Units made but not sellable first time
Setup scrap, process drift, in-process defects
Process control, first-piece checks, fixture wear
The three OEE factors and what each one is telling you.
The 85% figure, and what it is actually worth
You will be told that 85% OEE is world class and 60% is typical. Treat that as a rule of thumb, not a statistic — it circulates widely in lean and TPM material without a dataset behind it, and it was framed for discrete, high-volume, single-part production. A job shop running 40 changeovers a week cannot be judged by the same bar as a bottling line.
OEE
Common reading (rule of thumb)
What it usually means in practice
85% and above
World class for discrete manufacturing
Rare and usually only sustained on one dedicated line
60% to 85%
Normal for a plant that measures OEE
Real losses, mostly known, mostly fixable
40% to 60%
Typical of plants without shop-floor tracking
Downtime is being under-recorded, not absent
Below 40%
Data problem before it is a plant problem
Check the ideal cycle time and the downtime log first
Directional bands only. Compare an asset to its own trend, not to another plant.
The mistakes that make OEE unusable
Counting reworked units as good. Quality means first-time-through. If you count rework as good, quality loss vanishes and so does the reason to fix it.
Putting planned downtime into unplanned. Scheduled maintenance and unstaffed shifts come out of planned production time. Charging them to availability makes the number look bad for the wrong reason and pushes teams to skip PMs.
Missing micro-stops. Stops under a few minutes rarely get logged, so they surface as a low performance factor instead. That is why performance is usually the largest loss on a line nobody has instrumented.
Averaging OEE across a line. Multiplying or averaging the OEE of five machines describes nothing. Measure the constraint, because only the constraint's OEE converts into saleable output.
Changing the ideal cycle time mid-trend. Legitimate when the old one was wrong, but restate history or your chart tells a story that never happened.
TEEP and the 168-hour week
OEE judges the asset only during the hours you scheduled it. TEEP judges it against all 168 hours in the week: TEEP = OEE × (planned production time ÷ calendar time). The example scores 82.1% OEE but 47.9% TEEP, because the asset was scheduled for 840 of 1,440 minutes. Before buying a second machine, check whether TEEP says you already own the capacity — the capacity utilization calculator works that from the output side, an hour of constraint downtime gets priced in the downtime cost calculator, and quality losses feed the scrap and yield calculator.
Assembling the inputs is the slow part: planned time, logged downtime by reason code, produced quantity and scrap quantity per work centre per shift, sitting across work orders, operation completions, downtime records and inspection results. ERPray answers that as a question instead — "availability, performance and quality by work centre for the last 12 weeks" — computed from your own account, read-only, with the query printed underneath so your CI engineer can argue with the definition rather than the number.
Frequently asked questions
How do you calculate OEE?
Multiply three ratios. Availability is run time ÷ planned production time. Performance is (ideal cycle time × total units) ÷ run time. Quality is good units ÷ total units. With 793 run minutes of 840 planned, 1,412 units at a 30-second ideal cycle and 1,380 good, that is 94.4% × 89.0% × 97.7% = 82.1%.
What is a good OEE score?
85% is widely quoted as world class and 60% as typical, but that is a rule of thumb from lean literature rather than a measured benchmark, and it assumes high-volume discrete production. A high-mix job shop with frequent changeovers can run a healthy business in the 45–60% band. Judge an asset against its own trend.
Why is my OEE performance above 100%?
Because your ideal cycle time is too slow. Performance compares actual output to the theoretical maximum at the ideal cycle, so exceeding 100% means the asset beat the number you called ideal. Almost always the routing standard was used, which includes allowances. Replace it with the fastest cycle the asset has sustained for that part.
What is the difference between OEE and TEEP?
OEE measures the asset only during scheduled production time. TEEP measures it against all calendar time: TEEP = OEE × utilization, where utilization is planned production time ÷ calendar time. An asset at 82% OEE scheduled for 840 of 1,440 daily minutes has a TEEP of 48%, which is the honest answer to whether you need another machine.
Does planned downtime count against OEE?
No. Planned maintenance, unstaffed shifts, holidays and no-demand time are removed from calendar time to give planned production time, which is the denominator for availability. Only unplanned stops count against you. Charging PMs to availability penalises the maintenance you want people to do, and it shows up in TEEP anyway.
Should I calculate OEE per machine or per line?
Per asset for improvement work, and at the constraint for anything you report upward. Only the bottleneck's OEE converts into shippable units, so raising OEE on a non-constraint machine changes the chart and not the output. Never average OEE across machines — the average has no physical meaning.
This calculator needs you to find the inputs first. ERPray pulls them from your own ERP account and computes the answer live — with the exact query shown so you can check it.