How to Calculate OEE: Formula, Worked Example and Excel Sheet

OEE = Availability × Performance × Quality. A step-by-step example with a hypothetical shift, the source of the 85% world-class benchmark, common mistakes and an OEE sheet in Excel.

Translated from the Turkish original · Türkçe aslı

OEE (Overall Equipment Effectiveness) is calculated as the product of three ratios: OEE = Availability × Performance × Quality. Availability is the ratio of run time to planned production time; performance is the ratio of ideal cycle time multiplied by total count to run time; quality is the ratio of good count to total count. The shortcut: OEE = good count × ideal cycle time ÷ planned production time.

Below we walk through each part of the formula, a step-by-step example based on a hypothetical shift, where the 85% referred to as “world class” comes from, and how to build a sheet in Excel. We cover how to measure OEE automatically from cameras separately in our article on OEE measurement with cameras.

What is the OEE formula and what does it measure?

OEE shows how much of a machine's or line's planned production time is spent producing good parts at ideal speed. The concept became widespread through Seiichi Nakajima's work on Total Productive Maintenance (TPM) in Japan; today it is also included in ISO 22400-2, the standard that defines key performance indicators for manufacturing operations management. 100% OEE means producing throughout the entire planned time without any stops, at ideal speed and without a single defective part.

The three components answer three separate questions. Availability: did the machine run when it was supposed to? Performance: while it was running, did it run at the speed it should have? Quality: how much of the output was good the first time? Because OEE is a product, a loss in one component drags down the entire score; yet an OEE figure on its own does not tell you in which component the loss occurred. That is why OEE should always be reported together with its three components.

OEE has two close relatives. TEEP (Total Effective Equipment Performance) spreads effectiveness over the entire calendar time: TEEP = OEE × Loading, where Loading = Planned production time ÷ Calendar time. On a line running a single shift, OEE can be high while TEEP is low; the difference shows idle capacity. OOE (Overall Operations Effectiveness) is defined differently from source to source; the general idea is to add back to the denominator some of the time that OEE excludes by deducting it from planned production time, such as time the line is not run because there are no orders. If comparisons are to be made, the definition used should be written down.

How is availability calculated?

Availability = Run time ÷ Planned production time. Planned production time is found by deducting from shift time the periods in which no production is planned: meal and tea breaks, time the line is not run because there are no orders and, depending on the facility's definition, planned maintenance. Run time is found by deducting stops from planned production time: breakdowns, die and setup changes, waiting for material or an operator, and stopping the line for quality reasons.

The critical distinction here is this: a die change is an availability loss even if it is planned, because it can be shortened. Counting breaks as a loss, on the other hand, produces a meaningless target; no improvement effort aims to cut break entitlements. Fixing which time counts as outside planned production and which counts as a stop with a written list of definitions is the first step in making OEE comparable over time.

How is performance calculated?

Performance = (Ideal cycle time × Total count) ÷ Run time. Total count includes all parts, good and defective. Ideal cycle time is the shortest time that product can achieve per unit on that equipment under ideal conditions; it is taken from the machine's design speed, the verified shortest cycle or an engineering standard. The same calculation can also be done in terms of rate: Performance = (Total count ÷ Run time) ÷ Ideal rate.

Performance loss comes from two sources: the machine running slowly and minor stops. Minor stops are interruptions such as clearing a jammed part by hand or resetting a sensor, often too short to be written on the downtime form. That is why, in manually kept records, performance loss also hides unrecorded minor stops. If performance exceeds 100%, the error lies in the ideal cycle time; the chosen time is longer than the shortest time actually achievable.

How is the quality rate calculated?

Quality = Good count ÷ Total count. Good count means parts that meet specification the first time. A part sent for rework counts as defective even if it is eventually shipped, because it was not good the first time; otherwise the cost of rework never shows up in OEE. Scrap produced at line start-up and after a die change, until the settings stabilise, is also a quality loss.

The formulas for the components and OEE together:

Step-by-step OEE calculation example

All the figures below are examples; they show a hypothetical shift on a single press line. Shift time is 480 minutes. A 30-minute meal break and two 15-minute tea breaks are outside planned production.

1. Planned production time: 480 − 30 − 15 − 15 = 420 minutes.
2. Run time and availability: during the shift there were 25 minutes of breakdowns, 20 minutes of die change and 15 minutes of waiting for material, for a total of 60 minutes of stops. Run time is 420 − 60 = 360 minutes; Availability = 360 ÷ 420 = 0.857, or 85.7%.
3. Performance: the ideal cycle time is 30 seconds per part (0.5 minutes) and a total of 600 parts were pressed during the shift. At ideal speed, 600 × 0.5 = 300 minutes would have been enough for these 600 parts. Performance = 300 ÷ 360 = 0.833, or 83.3%.
4. Quality: of the 600 parts, 18 were scrapped and 12 went to rework. Good count is 600 − 30 = 570; Quality = 570 ÷ 600 = 0.95, or 95%.
5. OEE: 0.857 × 0.833 × 0.95 ≈ 0.679 (without rounding intermediate values), or about 67.9%. The shortcut serves as a check: 570 good parts × 0.5 minutes = 285 minutes; 285 ÷ 420 = 0.679.

Reading the same result in minutes shows better where the loss lies. Of the 420 minutes of planned time, 60 minutes were lost to stops, 60 minutes to slow running and minor stops, and 15 minutes to producing the 30 defective parts; what remains is 285 minutes of fully productive production. In this example, the stop loss and the speed loss are equal in size, but on manually kept forms usually only the stop loss is visible.

Where does the 85% world-class OEE benchmark come from?

The 85% figure does not come from an ISO standard; its source is the TPM literature. It is based on the targets mentioned in Nakajima's book on TPM (the English edition was published in 1988 as Introduction to TPM); according to the common account, companies in Japan that won the award given to plants successfully implementing TPM had OEE above 85%. The component breakdown appears in two forms in the sources; both round to 85%.

Before using this figure as a target, three things need to be taken into account. The first is differences in definition: when the definition of planned production time changes, the same line reports a different OEE, and another facility's 85% may not have been calculated with your definition. The second is differences in process: a small-batch workshop that changes products frequently and a continuous line pressing a single product should not be given the same target. The third is the quality component: 99.9% quality is a loose value for some processes and very hard to reach for others. In practice, the most meaningful comparison is your own line's history, measured with the same definition.

How do the six big losses reduce OEE?

The TPM literature groups the losses that reduce OEE under six headings and links each to a component. Those that reduce availability are breakdowns and setup and adjustment losses (die, tooling and product changes). Those that reduce performance are idling and minor stops, and reduced speed. Those that reduce quality are process defects, and rework and start-up losses (defective output produced until the line warms up and the settings stabilise).

The benefit of this classification is that it tells you which improvement tool to choose. If the share of breakdowns is large, the discussion turns to the maintenance plan and predictive maintenance; if the setup share is large, to a SMED effort that shortens die change time; if minor stops are large, to material supply and station layout. A tool being searched for at the station or material blocking the path is also reflected in performance as a minor stop; this is where the direct link between 5S implementation and OEE comes from.

What are the common mistakes in calculating OEE?

The first mistake is misclassifying planned stops. Deducting a die change from planned production time because it is “planned anyway” raises the score without any improvement. In the example above, if the 20-minute die change had been excluded, planned time would fall to 400 minutes and OEE would rise from 67.9% to about 71.3%. Conversely, counting breaks as stops artificially lowers the score.

The second mistake is using the wrong ideal cycle time. The most common error is treating the historical average cycle as ideal. In the example, if the observed average of 36 seconds had been used as the ideal cycle instead of 30 seconds, 600 × 36 seconds = 360 minutes and performance would appear to be 100%; the 60 minutes of speed loss would disappear from the table. In a shift where more than one product is made, each product's own ideal cycle should be used.

The third mistake is taking a simple average of percentages. When lines or shifts are combined, times and counts are summed and the ratios are recalculated from the totals. For example, if a line with 420 minutes of planned time ran at 80% OEE and a line with 60 minutes ran at 40%, the simple average gives 60%; the value calculated from the totals is (336 + 24) ÷ 480 = 75%.

The fourth mistake is counting reworked parts as good, and the fifth is not recording minor stops at all. The last is a natural consequence of manual data collection: a two-minute jam is not written on the form, but when it repeats dozens of times a day it can make up most of the performance loss.

How do you build an OEE sheet in Excel?

In Excel, a table in which each row is one shift of a machine or line is enough. In the column layout below, the formulas are written for the second row using English-language Excel function names and the comma separator.

Data entry columns: A Date, B Shift, C Line or machine, D Product code, E Shift time (min), F Time outside planned production (min; breaks, meals, no orders), H Stop time (min), J Ideal cycle time (s/unit), K Total count, L Defective count (scrap and rework).

Calculation columns: G Planned production time =E2-F2; I Run time =G2-H2; M Good count =K2-L2; N Availability =IFERROR(I2/G2,0); O Performance =IFERROR((J2*K2/60)/I2,0); P Quality =IFERROR(M2/K2,0); Q OEE =N2*O2*P2. In column R, enter =IFERROR((M2*J2/60)/G2,0) as a check; Q and R should give the same result. N, O, P and Q are displayed in percentage format.

Three additional settings make the sheet practical. The first is a separate downtime sheet: each row holds the start, end, duration and a reason code chosen from a drop-down list, and column H in the main table is summed from this sheet by shift and line using SUMIFS. The second: if there is more than one product in a shift, the ideal time is calculated with SUMPRODUCT from a per-product list of counts and ideal cycles. The third: in weekly and monthly summaries, columns G, I, K and M and the ideal time are summed, and the ratios are calculated from these totals. Any row in column O above 100% indicates that the ideal cycle definition needs to be checked; it can be flagged with conditional formatting.

Why is manually collected OEE data misleading?

An Excel sheet is only as accurate as the data that goes into it. On a downtime form filled in from memory at the end of a shift, start times are estimates, minor stops are missing, and the reason code is often whichever option is easiest to write. As a result, availability looks higher than it is, the loss hides in the performance component, and the improvement meeting is built around the wrong item. That is why capturing data automatically from the PLC, a machine signal or a manufacturing execution system (MES) is the second step of an OEE effort.

For older machines without a PLC and for manual stations, another option is the camera. CX Teknoloji's OEE solution derives machine stops, cycle time and parts set aside in the reject bin from the footage of existing IP cameras, without requiring any new sensors on the line; the operator tags the stop reason with a single tap, and the data is transferred to MES or ERP. Waiting and line-balance losses at stations are measured per station with PPA. The fastest way to see the gap between manually kept OEE and measured OEE on your own line is a single-line pilot.

Frequently asked questions

What is the OEE formula?

OEE = Availability × Performance × Quality. Availability is the ratio of run time to planned production time, performance is the ratio of ideal cycle time multiplied by total count to run time, and quality is the ratio of good count to total count. The same result can also be found via the shortcut good count × ideal cycle time ÷ planned production time; the two calculations coming out equal is a check on the accuracy of the sheet.

What is a good OEE value?

In the TPM literature, 85% is referred to as “world class”; its source is Nakajima's work on TPM, and the component breakdown is usually given as 90% availability, 95% performance and 99.9% quality. It is not a standard but a reference value. The definition of planned time, product variety and process type directly affect the score; the most meaningful comparison is your own line's history, measured with the same definition.

Are breaks and planned maintenance included in the OEE calculation?

Breaks and time the line is not run because there are no orders are deducted from planned production time, so they are not counted as losses. Die and setup changes, however, remain availability losses even when planned, because they can be shortened. How planned maintenance is treated varies from source to source; what matters is choosing a single written definition at the facility and applying it the same way across all lines and periods.

Why does performance go above 100%?

Performance exceeding 100% indicates that the ideal cycle time has been defined as longer than the shortest time actually achievable. The most common causes are treating the historical average cycle as ideal or using a single ideal cycle for different products. The ideal cycle should be taken per product from the machine's design speed or the verified shortest cycle; otherwise, speed loss disappears from the table.

What is the difference between OEE and TEEP?

OEE measures how effectively planned production time is used. TEEP spreads the same effectiveness over the entire calendar time: TEEP = OEE × Loading, where Loading = Planned production time ÷ Calendar time. A line running a single shift can show low TEEP despite high OEE. OEE is used for improvement on the shop floor, TEEP for capacity and investment decisions.

How is OEE calculated in Excel?

Shift time, time outside planned production, stop time, ideal cycle time, total count and defective count are entered into a table in which each row is a shift. Planned production time, run time and good count are found by subtraction; availability, performance and quality by division; and OEE by multiplying the three. Weekly summaries use the totals of times and counts, and the ratios are recalculated from these totals.