Despite being the most important metric when it comes to measuring manufacturing productivity, there is still a lot of misconception out there about observing and calculating OEE (Operational Equipment Effectiveness.)
In this article, we will discuss important OEE formulas to calculate OEE, as well as their applications. We will also learn how regularly measuring OEE can help improve OEE and productivity.
By the end of this article, you’d have learned about:
- The concept and definition of OEE
- Three different components of OEE and how to calculate each of them
- The formula for calculating OEE
- OEE calculation example
- Why regularly monitoring OEE is important to improve productivity
- Best practices on how to drive up OEE
Let us begin from the basics: what is OEE
What is OEE?
OEE, which stands for Overall Equipment Effectiveness, is a metric used to measure how effective a manufacturing process is executed compared to its full potential during its Planned Production Time.
OEE was coined by Seiichi Nakajima as a part of his TPM (Total Productive Maintenance) methodology. OEE identifies the percentage of manufacturing time that is productive while considering three different elements: availability, performance, and quality.
An OEE score of 100% means the manufacturing process runs without interruption throughout the whole Planned Production Time (100% availability), constantly at its theoretical maximum speed (100% performance), and only produces good, non-defective products/parts (100% quality.)
Factories and any companies with manufacturing processes should strive to regularly measure their OEE (ideally in real-time,) with OEE being the gold-standard metric for bench-marking the progress of the manufacturing process, identifying losses, reducing/eliminating waste, and improving the productivity of manufacturing equipment.
By measuring OEE and the underlying losses, the company can gather valuable insights into how it can improve its manufacturing process to be more effective, efficient, and productive.
How to calculate OEE
The OEE of a manufacturing process is calculated as a product of its three key components: Availability, Performance, and Quality, with the following formula:
OEE= Availability x Performance x Quality
- Availability: the percentage of time that the equipment is available to operate compared to the Planned Production Time. 100% Availability means the equipment is always available throughout the scheduled time to operate.
- Performance: the speed at which the equipment operates as a percentage of its theoretical maximum speed. 100% Performance means the machine operates consistently at its maximum speed throughout the Planned Production Time.
- Quality: the percentage of Good Units produced compared to the Total Units produced. A 100% Quality score means the manufacturing process only produces good/non-defective units.
Below, we will discuss the formulas for calculating each of these components, starting from the Availability score.
Calculating Availability score
Availability is affected by two types of losses: Planned Stops and Unplanned Stops
Planned Stops are any significant period of downtime in which the equipment stops operating due to a planned reason, such as changeovers, quality inspections, planned maintenance, or adjustments.
Unplanned Stops are any significant downtime in which the equipment is scheduled for production but is not running due to some type of equipment failure (i.e., breakdowns, materials shortage, etc.)
With that being said, Availability score can be calculated with the following formula:
Availability= Actual Production Time / Potential Production Time
A machine is scheduled to run for one full (8-hour) shift. There are two instances of planned maintenance, each for 30 minutes, and there is a total of 55 minutes of downtime due to machine failure.
From the above example, we can identify the following variables:
- Potential Production Time: refers to the total time that the shift was scheduled to run, which is 8 hours or 480 minutes
- Planned Stops: 2 x 30 minutes, or 60 minutes in total
- Unplanned Stops: a total of 55 minutes
- Actual Production Time = Potential Production Time - Planned Stops - Unplanned Stops = 480 - 55 - 60 = 365 minutes
Availability = 365 minutes / 480 minutes = 76.04%
Calculating Performance score
Performance is also affected by two types of losses: Small Stops and Slow Cycles.
It could be difficult to differentiate Small Stops from Planned/Unplanned Stops (which are Availability losses,) so it’s important to decide on a clear threshold to differentiate the two. For example, the company can decide that any stops that occur under 5 minutes are considered Small Stops, and those longer than 5 minutes are either Planned or Unplanned Stops.
Possible causes of Small Stops including clogged materials, quick cleaning, blocked/misaligned sensors, and more.
Slow Cycles, on the other hand, are situations in which the equipment runs slower than its Ideal Cycle Time (the theoretical maximum time an equipment requires to manufacture one unit.) Slow Cycles can be caused by various reasons, including but not limited to poor environmental conditions, operator error, poor lubrication, substandard materials used, etc.
With that being said, Performance can be calculated with the following formula:
Performance = Actual Output / Theoretical Output
The machine has an Ideal Cycle Time of 10 seconds (meaning, it can produce 6 units per minute) and has an actual production time (the same as the previous example) of 365 minutes. During this 365 minutes of actual production time, the machine produces 2083 units.
Therefore we can get the following variables:
- Theoretical Output = Actual Production Time/ Ideal Cycle Time = 21,900 seconds / 10 seconds = 2,190 units
- Actual Output = 2,083 units
Performance = 2,083 / 2,190 = 95.11%
Calculating Quality score
Quality score is affected by two types of losses: Production Rejects and Startup Rejects.
Every piece of equipment requires a startup (or warmup) period. Defective units produced from the startup period until the stable production period is reached are called Startup Rejects.
Startup Rejects are caused by suboptimal startup (changeover,) misconfiguration, or long warm up cycles. There are also machines that naturally produce waste after startup.
On the other hand, Production Rejects are any defective units produced during the stable production time. Common reasons for Production Rejects include operator errors, materials expiration, or incorrect equipment configurations.
Quality score can be calculated with the following formula:
Quality = Good Unit Output / Actual Output
Continuing the same example we’ve used above:
The total number of parts produced during this shift is 2,083 units, which include both good and bad units. Out of these, the number of units declared as rejects are 103.
Thus, we can figure out the following:
- Total Output during this shift is 2,083 unit
- Good Unit Output: The actual number of good parts produced is 2,083 - 103, so 1,980 unit
Quality = 1,980 / 2,083 = 95,05%
Calculating Overall Equipment Effectiveness
Now that we’ve got each of the Availability, Performance, and Quality score, we can finally calculate the OEE score as follows:
OEE = Availability Score x Performance Score x Quality Score
Or we can also use the more detailed formula as follows:
OEE = (Production Time / Potential Production Time) x (Actual Output / Theoretical Output x (Good Unit Output / Actual Output)
OEE = 76.04% x 95.11% x 95,05%
Since percentages cannot be multiplied, we should convert each percentage score to a decimal, so:
OEE = 0.7604 x 0.9511 x 0.9505
OEE = 0.6874
OEE = 68.74%
What is a Good OEE Score?
The theoretical gold standard for a good OEE score is cited as 85%, or often deemed as “world-class” OEE.
However, those who have monitored their OEE regularly for quite some time will soon learn that striving for this 85% world-class OEE score isn’t always realistic and, in fact, can be counterproductive.
Why is that so?
Let’s go back to the basic formula for calculating OEE, which is:
OEE = Availability x Performance x Quality
The thing about this formula is even if a manufacturing process scores 90% for each of Availability, Performance, and Quality, it would only get 72.9% in OEE, still far away from the 85% “target” score.
In fact, the average score for most factories all around the world—including some really good ones—is ‘only’ between 60% and 70%.
Instead, when deciding on a target for the OEE score, it’s best not to focus on an arbitrary number but rather on consistently improving.
Monitor your current OEE score, and try to incrementally but steadily improve from this score. Set targets that are realistic and meaningful for your business; each incremental milestone should be attainable every couple of months—not too soon to seem insignificant, but not too long so that you lose engagement from your team.
Yet, throughout this incremental process, it’s important, to be honest. That is, even if your current true OEE score is disappointing, don’t be too discouraged with it, and even worse, don’t try to hide it. See your current state of OEE as an opportunity to improve
Using OEE as a tool for improving productivity: Implementation
It’s easy to be tempted to look at OEE as a vanity metric and lose sight of why we should measure it in the first place.
Monitoring the OEE score on its own is not actually very helpful in improving productivity. Instead, we should focus less on the OEE score and more on fixing the underlying OEE losses.
OEE can be a powerful top-level analytical tool by breaking down OEE into its three underlying components: Availability, Performance, and Quality.
However, knowing the scores for each of these components alone won’t tell you much about what you need to do to improve OEE. Instead, the true value of OEE comes from the ability to act on the underlying losses for each component: Availability Losses, Performance Losses, and Quality Losses.
Each component has two types of major losses (making it six losses in total), so they are often referred to as the Six Big Losses.
Unplanned Stops (Downtime)
Planned Stops (Changeovers)
Below, we’ll discuss each of these Six Losses one by one and give some examples of actions you can implement to eliminate each loss.
1. Availability Loss: Unplanned Stops
An Unplanned Stop, or Downtime, refers to a period of time above a certain threshold in which the equipment is scheduled for production but is not running due to an unplanned reason.
Having this threshold is important since we’ll need to differentiate between Unplanned/Planned Stops, which are Availability losses, and Small Stops, which are Performance Losses. A downtime shorter than this threshold is a Small Stop.
Unplanned Stops typically happen due to various types of equipment failures like breakdowns, tooling failures, and so on. However, operator errors (or lack of operators) and lack of materials are also common causes of Unplanned Stops.
The most effective way to minimize Unplanned Stops is to track the underlying reasons so you can fix each of them respectively. A common method is to assign Reason Codes for different downtime causes and monitor the occurrence of each Code.
2. Availability Loss: Planned Stops
The most common causes for Planned Stops are changeovers (or setups) or other types of equipment adjustments (tooling adjustments, regular cleaning, warmup time, quality inspections, etc.)
Changeovers (or setups) are typically the largest sources of Planned Stops, and one of the most effective methods to address Planned Stops is by implementing SMED (Single-Minute Exchange or Die).
3 Performance Loss: Slow Cycles
Slow Cycles refer to the time when equipment runs slower than its Ideal Cycle Time, whereas Ideal Cycle Time is the theoretical fastest time for the equipment to manufacture a unit.
Some of the most common reasons for Slow Cycles are:
- Accumulation of dirt/debris
- Wear and tear
- Poor lubrication
- Poor materials used
- Environmental conditions
- Operator errors
- Longer/too frequent startups
Ensuring the equipment, operator, and environment are in optimal conditions is the key in minimizing Slow Cycles.
4. Performance Loss: Small Stops
Small Stops account for the time when the equipment experiences downtime for a short period of time under the agreed threshold.
Some common reasons for Small Stops are material jams, obstructed manufacturing flow, incorrect configurations, blocked sensors, and so on.
Identifying the underlying Small Stops cause is crucial in improving Performance Score.
5. Quality Loss: Startup Rejects
Accounts for defective units produced from the equipment’s startup until the state of stable production is reached.
Common underlying causes for Startup Rejects include incorrect settings and non-optimal startup. However, there are machines that naturally create waste during the startup/warmup period.
6. Quality Loss: Production Rejects
Defective units produced during the stable production period.
Examples of common reasons for Production Rejects include incorrect misconfigurations, operator errors, materials expiration, and so on.
Why monitoring OEE is crucial for improving productivity
As we can see from studying the formulas for calculating OEE above, OEE is actually a holistic metric that combines measurements of availability, performance, and output quality; all three are the most important elements of manufacturing productivity.
With that being said, monitoring OEE will provide the following benefits:
- Allowing you to quickly identify and prioritize problems
By regularly monitoring OEE in real-time, you can quickly identify any losses and conditions that may lower your OEE and overall performance, so you can more quickly resolve this situation. By measuring the three different components of OEE, you may also identify multiple losses in multiple areas, allowing you to prioritize more critical issues that demand immediate attention. For example, if you identified that you are using sub-par material that may significantly lower your product’s quality, then it may require more immediate attention than when you identified that a machine is experiencing slow cycles once every shift.
- Improving transparency and accountability of your team
Don’t forget that human factors can also play a significant part in your manufacturing productivity. Real-time monitoring of your OEE will allow you to easily monitor what’s going on with your equipment at the moment, including operator errors. This will improve the transparency of your whole manufacturing process while at the same time keeping your team members accountable for improving OEE and overall productivity.
- Fix quality issues as soon as possible
By monitoring your OEE, you don’t have to wait until the end of your production line to identify quality losses. By utilizing sensors and other means, you can get notified when there are any quality deviations in your manufacturing process as soon as they occur. This will ultimately allow you to fix any quality losses as soon as possible and improve your OEE in the process. Not to mention, by correcting quality deviations immediately, you can keep your customers happy by always getting the quality they expect from your products.
- Optimize manufacturing performance
Real-time monitoring is the best way to improve the performance component of your OEE. By knowing how your machine operates in real time and monitoring its performance, you can resolve any issues and eliminate bottlenecks as soon as possible. This way, you can keep your manufacturing process running at its optimal level consistently.
- Enabling preventive maintenance
Real-time monitoring allows you to perform preventive condition-based maintenance on your equipment and manufacturing assets to minimize downtime. When, for example, your sensors identify potential emerging issues, you can perform quick maintenance before the machine slows down—or worse, fails. Preventive maintenance will especially improve the availability component of your OEE.
Above, we have discussed the important formulas you should know to calculate OEE, as well as the best practices and tips on how to incrementally improve your OEE score.
Yet, it’s important not to get hung up on the technical details of OEE too much, but instead, you should focus on achieving incremental improvement and fixing underlying issues that impact your OEE.