What is OEE?

OEE (overall equipment effectiveness) measures how much of a machine’s planned production time turns into good parts made at full speed. It multiplies three factors: availability asks whether the machine ran when it was scheduled to, performance asks whether it ran at its ideal cycle time, and quality asks whether each part was good the first time.

The definitions below follow the common TPM calculation that most plants use. One shift on a CNC lathe is worked through by hand, and two presses show what a single OEE number hides.

What OEE measures#

OEE came out of total productive maintenance (TPM), the program Seiichi Nakajima led in Japan from the early 1970s.^[3] The glossary entry for OEE gives the same three factors in IoTFlows’ terms.

The product collapses into one ratio. Fully productive time is the time a machine would need to make only its good parts, at the ideal cycle time, with no stops.^[1]

For example, a CNC lathe that makes 170 good parts on a 2-minute ideal cycle has produced 340 minutes of fully productive time. Over 450 planned minutes, its OEE is 75.6%. The rest of this article explains where the other 110 minutes went.

The three OEE factors#

Each factor isolates one kind of loss, so each one points to a different fix.

Availability#

Availability is run time divided by planned production time.^[1] Planned production time is the shift less the time nobody intends to run the machine, such as breaks, meetings, a maintenance window with the machine scheduled off or a shift with no orders.

Changeovers and setups stay in. A changeover is a planned stop, but the machine was meant to be producing during it, so it counts against availability.^[1] For example, a 20-minute die change on a 450-minute shift costs 4.4 points of availability on its own.

Planned maintenance is where plants draw the line differently. The six big losses count planned maintenance as a planned stop inside availability.^[2] Take it out of planned production time only when the machine is scheduled off for the whole window, the way a weekend preventive maintenance slot is.

Write the rule down once and apply it to every machine. A breaks-only rule on one machine and a breaks-and-changeovers rule on another make their OEE impossible to compare.

Performance#

Performance compares the parts a machine made with the parts its ideal cycle time allows in the time it ran.^[1] The ideal cycle time is the best cycle the process sustains in good conditions: not the fastest cycle ever recorded, not the shift’s average and not the quoted one.

Performance catches what availability misses: slow cycles and stops too short for anyone to log. For example, a press running 40 strokes a minute against an ideal of 60 runs at 66.7% performance while its status light stays green all shift.

Performance above 100% means the ideal cycle time is set too slow.^[1] Fix the ideal cycle time, not the result: time 10 to 20 consecutive cycles of each operation on a good day and use the best sustainable cycle.

Quality#

Quality is good parts divided by total parts. A good part passes the first time, so a part that needs rework counts as bad even when it ships.^[1]

For example, a molding cell that makes 2,000 parts, scraps 30 and reworks 50 has quality of 96.0%, not 98.5%. Counting reworked parts as good raises OEE and hides what the rework costs.

Work one shift through#

Take one shift on a hypothetical CNC lathe and calculate each factor in order.

The short form gives the same answer: 170 good parts × 2 minutes = 340 minutes of fully productive time, and 340 ÷ 450 = 75.6%.

Read the losses in minutes, not points. Stops cost 54 minutes, slow cycles 44 and scrap 12. The 36-minute setup is two thirds of the stopped time, so a faster changeover is the first project on this lathe, and the 44 slow minutes are the second. For more shifts worked step by step, see how to calculate OEE.

The six big losses#

TPM sorts every lost minute into six losses, two for each factor.^[2] Assign each minute to exactly one loss, never two, so the three factors still multiply to the right result.

Decide where a minor stop ends and a logged stop begins, for example at 2 minutes, and keep that line fixed.^[2] Otherwise the same jam moves between availability and performance from one week to the next.

What OEE tells you, and what it hides#

A single OEE percentage tells you how much time a machine lost. The three factors tell you what kind of time it lost, and that decides the fix.

For example, two 200-ton presses each read 65.8% OEE. The first runs at 70% availability, 95% performance and 99% quality, so it loses its time to stops. The second runs at 95% availability, 70% performance and 99% quality, so it loses its time to slow strokes and jams. The first press needs reasons on its stops; the second needs a look at its feed and its ideal cycle time.

The multiplication also compounds small losses. Three factors at 90% each give an OEE of 72.9%, not 90%.^[3]

Use OEE to:

• Find the largest loss on each machine, first by factor and then by the six losses.
• Find the machines that limit output. A point of OEE lost on the bottleneck costs the whole line, while the same point on a machine with spare capacity may cost nothing.
• Check whether a change worked, by comparing the same machine before and after. Leggett & Platt Aerospace lifted OEE on the most problematic CNC lathe in a cell from 39% to 45% after a TPM program that included training its maintenance crew.^[5]
• Price quality in machine time. Scrap shows up as lost minutes beside stops and slow cycles, so you can rank all three on one scale.

The glossary defines utilization the way IoTFlows measures it, from the sensor alone.

Benchmarks and world-class OEE#

An OEE of 85% is often called world class.^[3] Nakajima set his world-class figures from practical experience as minimums for companies to strive for, not as a measured average across plants.^[3]

Reaching 85% takes high marks on every factor. For example, 90% availability, 95% performance and 99% quality multiply to 84.6%.

Definitions differ too. Schiraldi and Varisco found that the ISO 22400 standard gives two definitions of OEE that appear to diverge from each other and from Nakajima’s original formulation.^[4] Two plants can report different OEE for the same line, depending on whether changeovers sit inside planned production time and how each sets its ideal cycle times.

Compare a machine with its own history before you compare it with a benchmark. Set the first goal a few points above your own baseline, as the guide to choosing an OEE goal describes, and raise it when the machine improves.

Track OEE factor by factor#

IoTFlows measures availability and performance from a magnet-mount SenseAi on each machine, with no PLC connection. The sensor decides running or stopped every second, and Uptime, running time over running plus stopped inside your shifts, gives availability. The parts gauge gives performance: parts counted against what the ideal cycle time allows in the running time. Quality reads on Shift Production as good parts over everything counted, from the scrap operators log with a reason. One OEE goal colors every gauge green or red.

The metrics reference defines each number, and OEE tracking shows the screens.

I use the dashboard every day to compare and validate actual cycle times against the times listed in our bills of material.

Start measuring OEE#

You don’t need software to calculate OEE for one machine. You need a clear rule for planned time, an ideal cycle time and an honest count.

1. Choose the first machine

   Start with the machine that limits your output, because its losses cost the whole line.

2. Define planned production time

   Write down which time comes out, such as breaks, meetings and maintenance windows with the machine scheduled off, and keep changeovers in. Use the same rule on every machine.

3. Set an ideal cycle time per operation

   Use the best cycle the machine sustains on each part, timed at the machine, not the quoted cycle time.

4. Capture run time and part counts

   Record stops and counts by hand or from a sensor. A paper log holds the stops someone wrote down; a sensor records every one. The guide to manufacturing data collection compares the ways to get them.

5. Log scrap with a reason

   Record each bad part at the machine when it happens, with the reason, so quality and its causes come from the same entry.

6. Review the factors every week

   Rank the week’s losses by minutes, fix the largest, and check the same machine’s factors the following week.