Asset Efficiency vs OEE —
When They Match, and When They Won't
On a plant that runs around the clock, a simulated Asset Efficiency and a reported OEE can land within a point of each other. On a plant that runs one staffed shift, the same two numbers can differ by thirty. Nothing changed but the denominator.
A plant engineer once asked us whether our Efficiency figure was based on 24/7 possible asset utilization, the way their TEEP metric is, or on 24/5 production time. It is a sharper question than it looks, and it is the one worth settling before anybody compares a model against a dashboard in a meeting.
Because they will. Someone will put a simulated Efficiency next to the plant's OEE, see a gap of twenty or thirty points, and conclude that the model is broken. Usually the model is fine. The two numbers were simply measured against different amounts of time.
One shift, two denominators
Take a line that runs at an ideal rate of 100 units per minute. It is staffed for a 900-minute operating window — sanitation and the unstaffed shift are outside it. Over one day it produces 72,000 units.
Now measure that same output two ways.
The same 72,000 units, measured twice
| Basis | Time counted | Potential output | Result |
|---|---|---|---|
| Staffed operating window what the line was asked to do |
900 min | 100 × 900 = 90,000 | 80.0% |
| A perfect day what the asset could theoretically do |
1,440 min | 100 × 1,440 = 144,000 | 50.0% |
Nothing about the shift changed between those two rows. The line produced exactly the same units. The only thing that moved was how much time the denominator was willing to count — and that alone is worth thirty points.
This is why a model and a dashboard disagree. The plant's number is usually measured against the hours it staffed. A simulation's Efficiency is usually measured against the hours the asset physically had. Put them on one chart with one 100% line and the picture invites a comparison that the arithmetic does not support.
Where each number comes from
OEE — against the time you planned to run
OEE multiplies three factors: Availability × Performance × Quality. Its denominator is planned production time. Deliberately not running — an unstaffed third shift, a scheduled sanitation window, a plant holiday — does not count against it, because you never planned to produce then.
That makes OEE the right measure of how well you executed the plan you made. It is silent on whether the plan itself left capacity on the floor.
TEEP — against all the time there is
TEEP takes OEE and multiplies it by Utilization, the share of calendar time you chose to schedule. Its denominator is every hour the asset existed, whether staffed or not. A line running beautifully on one shift can post excellent OEE and mediocre TEEP at the same time, and both are true.
TEEP answers the capital question: how much of this asset am I actually using?
Asset Efficiency — production over potential, across the modeled period
A simulation reports the ratio it can defend: units produced, divided by units the line would have made at its ideal rate with no interruptions, over the period modeled. It is TEEP-shaped in construction — it counts time you were not staffed — but it is not textbook TEEP, because the horizon is the modeled period rather than a rolling 24/7 calendar. Model one production day and no weekend hour is credited or debited.
Efficiency answers: of everything this line could physically have made, how much did it make?
What about quality?
OEE's third factor is Quality — the share of output that was actually saleable. It is easy to assume a simulation ignores this and counts every unit the line pushed out, which would make the two numbers incomparable on a second axis as well as the first.
It doesn't have to. Several block types — and sets of blocks arranged as a construct — can be designed to represent scrap or rework. Model it and the simulation removes or recirculates rejected units the way the line does, so what it reports is good output. The Quality factor is then already inside the numerator, exactly where OEE puts it.
That matters more than it sounds. It means a simulated Efficiency with scrap modeled is the same measurement as OEE with a different denominator — not a loosely related figure. Availability shows up as interrupts, Performance as rate loss, Quality as modeled scrap or rework. All three factors are represented. Only the time basis differs.
If quality is not modeled, the gap runs both ways. The simulated numerator then counts units the plant would have rejected, which pushes Efficiency up, while the wider denominator pushes it down. Two errors in opposite directions are far harder to explain in a meeting than one. Before comparing anything to a plant number, check whether scrap or rework is represented at all.
Scrap and rework are not interchangeable here. A scrapped unit leaves the count; a reworked one comes back and is eventually good. If the plant's Quality factor is first-pass yield, a model that recirculates rework will read slightly high against it — worth checking before the two are set side by side.
When the two numbers converge
There is one case where the gap disappears completely: a plant that genuinely runs 24/7.
Schedule every hour and Utilization goes to 100%. TEEP collapses onto OEE, because there is no unscheduled time left for the wider denominator to count. A simulated Efficiency measured against a perfect calendar and a plant's OEE measured against planned time are then dividing by the same number, and they should agree.
They do. On a continuous 24/7 operation modeled over a full year, our simulated Efficiency has come within 1% of the plant's reported figure. That is the strongest check available on the whole approach: strip out the definitional difference and what remains is the model itself — and it holds against a year of real production.
And it holds mode by mode, not just in total. The chart below plots observed availability against simulated availability for every interrupt on a line — one marker per failure mode — against a y = x match line.
This is the part that makes the overall number trustworthy. A single aggregate can land on the right answer for the wrong reasons — one mode overstated, another understated, the errors quietly cancelling. A per-mode scatter cannot hide that. Points sitting on the match line across the full range mean each failure mode was reproduced on its own terms, so the total is right because the parts are.
Which is also why the disagreements happen. A twenty- or thirty-point gap is not evidence that the simulation is wrong. It is evidence that the plant is not running 24/7, and that the two denominators have parted company. The further a plant is from continuous operation, the wider the gap — predictably, and by exactly the amount of time it chose not to schedule.
Which number to use, and when
- Judging the shift you ran — use OEE. It measures execution against the plan, which is what a shift team controls.
- Judging whether to buy another line — use Efficiency or TEEP. If you are at 50% of physical potential, a second line may be the most expensive way to solve a scheduling problem.
- Comparing a model to history — use neither ratio. Compare the quantities. Units produced against units produced needs no denominator at all, so there is nothing to disagree about.
The practical rule: never put a simulated Efficiency and a reported OEE on the same axis against the same 100% line. A footnote explaining the difference will not survive contact with the chart — the picture is more persuasive than the caption, and the picture will be wrong.
The short version
OEE asks how well you ran the hours you scheduled. TEEP and Efficiency ask how much of the asset you used at all. The same shift can be 80% by one measure and 50% by the other, and both numbers are honest — they are simply counting different amounts of time.
When a model and a dashboard disagree, check the denominator before you check the model. It is nearly always the denominator.
Related: Efficiency in the ReliaSim docs · How interrupts are modeled · How to find the real bottleneck on a production line · The ReliaSim method · Constraints, buffers and interrupts
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