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OEE: Definition, Factors And Calculation – with Examples

Uwe Kobbert • April 16, 2021
OEE: Definition, Factors And Calculation – with Examples
This article explains in detail how to calculate the OEE metric and its constituent factors. We’ll look at the formulas and explain the calculations with the aid of examples. Once you’ve worked through this article, you’ll have a full understanding of how OEE works. OEE, short for Overall Equipment Effectiveness, is a measure of a manufacturing operation’s productivity.
 
Before we delve into OEE and the individual factors it considers, however, first we should make it clear that OEE only considers planned production time. The time period considered for calculating OEE is planned production time.
 
What exactly does this mean? Your machines are physically available to produce the entire time (24/7). In other words, theoretically they could run nonstop around the clock. In actual practice, however, there will always be interruptions (= planned time losses) due to holidays, breaks, a lack of orders, and/or planned stops.
  • Planned unavailability
  • Planned stops
These “losses” are taken into account for calculating the “Total Effective Equipment Performance”, or TEEP, but not for the OEE metric, which only considers losses that occur during planned production times.
 
Now that this has been explained, let’s take a closer look at the three OEE factors, each of which quantifies a different kind of loss.
 

1. Availability

Availability is the time during which your machinery actually runs, expressed as a percentage of the planned operating time.
 
availability_formula
 
To calculate availability, divide the actual time worked by the total planned operating time. Then multiply this ratio by 100 to obtain a percentage:
You already know a machine’s planned running time from the production schedule. But how do you determine the actual time worked?
 
You do this by adding up all the stops and subtracting them from the sum of the planned operating times.
 
Analyzing the data on downtimes sheds light both on their causes and on the potential for making improvements.
 
You are also enabled to see the cumulative effect of all the “micro-stops” that occur over the course of a day. How stops impact a system’s overall availability is quickly apparent. And you can leverage this knowledge to plan production better.
 
It turns out that most stops are caused by a fairly small number of factors. Depending on the machine and process, these can vary considerably. The important thing to realize, however, is that careful analysis usually reveals just a few main culprits. As is so often the case, the Pareto principle also applies here: 20% of the causes are responsible for 80% of the outcomes.
 
availability_example_en
 

2. Performance

To calculate performance, you have to find out how many units you have produced and compare these to the number of parts that you could have manufactured during the actual (not planned, but actual!) operating time by running your machines at the fastest possible speed.
 
Here’s the formula:
 
performance_formula_en
 
Actual performance:  It’s very simple to determine how many units a machine has processed or produced. Just be sure to count all of them, including rejects.
 
Target performance:  Multiply the maximum number of manufactured parts per hour by the time during which the machine actually operates.
 
How do you determine your maximum output (performance target)?
 
A machine’s manufacturer usually provides this information in the form of an “ideal cycle time”, which you can use to derive your performance target.
 
Example: If two parts are produced per cycle and the ideal cycle time is five seconds, then 24 parts ought to be made in a minute and 1440 in an hour.

If this information isn’t available, identify the fastest cycle time that has been recorded since the machine has been in use. Then calculate how many units you could produce if your machines constantly ran at that speed. 
 

3. Quality

Quality is the third of the three OEE components that need to be calculated. Quality is defined as the share of good parts, i.e. those that meet the quality requirements, out of the total number of produced parts.
 
quality_formula_en
 
In practice, you can usually determine the number of good parts by subtracting the number of rejected and reworked components from the known number of parts produced during a given time period.
 
Total manufactured parts = good parts + rejects + reworked parts
 
Professional monitoring of the quality metric helps you concentrate on resolving your main quality problems.

Typically, questions like these are asked:
  • What are my most common quality problems?
  • Who or what causes them?
  • Do quality problems tend to cluster?
It’s obvious that defective parts significantly affect manufacturing costs and on-time delivery. Identifying problems at an early stage of the value creation process helps limit the damage.
 
quality_example_en
 
Don’t confuse the level of quality with another quality metric called first-pass yield or FPY. It indicates the number of parts or assemblies that are flawlessly completed in the first production pass – in other words, without any rework.
 

4. OEE Formula

Now that we’ve familiarized ourselves with all three OEE factors, it’s simple for us to correctly calculate the OEE metric: simply multiply together all three factors!
 
oee_formula_en-1
 
The following graphic shows the whole process at a glance.
 
oee_factors_matrix_en
 

Conclusions

Now you know how to calculate the OEE metric from the three factors by yourself. Well done! However, this is just the first step toward achieving a full understanding of OEE.
 
The acquisition of the OEE is part of the production data acquisition (PDA), in which a larger scope of technical and organizational data is covered.
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If you have any questions or need help with the OEE basics, our experts will be happy to coach you and answer your questions.
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