What is OEE? Definition, use and best practices

It's a topic of discussion everywhere in the workshops. Strategic decision-making regarding production often relies heavily on this master indicator, the OEE (Overall Equipment Effectiveness)!

An Indicator to Rule Them All? Let's Discover It Together.

OEE definition

A production machine represents a significant investment, so optimizing its use is strategic for a company.

To track the productivity of these costly equipments, there is a complete array of indicators that vary in generality and precision.

OEE, or Overall Equipment Effectiveness, is the industry's benchmark indicator, originating from the term "Overall Equipment Effectiveness."

This indicator allows to:

📊 Measure performance

🔎 Facilitate company management

💡 Make decisions and implement action plans

Using OEE, we measure the overall performance of industrial equipment.

The goal is to gather various types of information, thus enabling the analysis of the main causes of performance loss (operational status, consideration of production stops, pace, rejected pieces, etc.).

OEE origins

Calculating it is simple: divide the number of correctly manufactured pieces by the number of pieces that the machine should have produced in its theoretical production time, taking into account the cycle time of one piece.

This precise calculation was developed by a group of industry professionals who wrote a standard that standardizes the different methods of calculating indicators: the AFNOR-NFE 60-182 standard was created in 2002.

How is It calculated?

To calculate the Overall Equipment Effectiveness (OEE), simply divide the total actual production time of conforming pieces by the total theoretical production time:

Calculation:

OEE = Total conforming production time / Total theoretical production time

i.e., Actual Time / Required Time

➡️ There is a second method of calculation, which involves multiplying the following three indicators to obtain the OEE: Performance x Quality x Availability

But to get it, we need to know the following three components:

1. Performance Rate measures performance deviations due to pace variations (under or over speed) and micro-stops. A machine that idles or accumulates micro-stops will have reduced performance.

2. Quality Rate measures productivity losses related to the production of pieces that do not meet quality requirements. It is therefore affected by the number of pieces declared non-conforming (rejects and rework).

3. Operational Availability measures productivity losses related to unplanned stops: breakdowns, waiting, series change, etc. The higher this rate, the more available your machine is for production.

OEE results from the multiplication of these three indicators, all ranging between 0 and 100%. The closer the OEE is to 100%, the more efficient the production.

EXAMPLE ➡️ A machine with an OEE of 80% has produced good parts for its client 80% of its production time.

Practical Case: OEE at "Factory K"

For our example, we consider the following elements:

✔️ "Factory K" is a manufacturer machining mechanical parts.

✔️ Ideal production time for 1 conforming piece is 10 minutes.

✔️ The workshop is open from 5 am to 10 pm, the teams have 15 minutes of break in the morning and afternoon as well as 1 hour for lunch between team shifts.

✔️ There were 2 tool changes and adjustments of 30 minutes each.

✔️ We count 1 daily recurring breakdown lasting 1 hour.

✔️ Due to 2 material absences of 30 minutes, the machine stopped twice.

✔️ Due to tool wear, the production pace decreased and required 2 more hours.

✔️ Factory K's machine produced 55 pieces, 8 of which were non-conforming on the analyzed day.

Let's calculate together the OEE of Factory K:

📌 Total Time = 24h or 1,440 min

📌 Opening Time = 17h or 1,020 min

📌 Required Time = 15h30 or 930 min

📌 Operating Time = 12h30 or 750 min

📌 Net Time = 10h30 or 630 min

📌 Useful Time = 9h10 or 550 min

Calculation:

OEE = 550 / 930

i.e., Useful Time / Required Time

59%

Impact of Improving OEE

We can only improve what we can measure! Measuring all components of OEE is complex and requires collecting a lot of information daily.

To simplify this collection and thus improve its OEE, Factory K could deploy a 4.0 production tracking solution within its workshop.

Thanks to its digitalization, Factory K would automate its production data collection and could identify the various causes of unplanned stops that occur during its production. This would allow it to set up an improvement plan to reduce these stops and more generally the losses!

Exceptions: Does a Low OEE Equal Poor Production?

Not necessarily! The Overall Equipment Effectiveness (OEE) can vary greatly between organizations and industries. It depends on production processes, the environment, and various control methods.

For a company manufacturing complex parts from hard materials with numerous checks during the production process, a good OEE might start at 50%.

Conversely, a high-paced production relying on a lean logistics system will aim and manage to maintain an OEE above 95%.

A good OEE cannot be judged the same way across different sectors or production typologies. However, it can always be improved once it is analyzed!

To calculate OEE, data collection is essential.

But how? It's easier than you think!

Many organizations still collect their data manually. Necessary for the smooth operation of a workshop, these data are most often compiled in spreadsheets. This method is not only cumbersome but also not straightforward.

Manual data entry is time-consuming for operators and managers alike. Faced with the re-entry of information, real-time data reading, which might contain errors, is not possible.

To minimize discrepancies and facilitate reliable data collection, new connected tools have emerged, particularly IoT production monitoring solutions.🤖

4.0 Production Monitoring Solution