Choose your starting point
01
Understand the OEE formula: This is how to calculate OEE
02
Determine availability with the OEE formula: This is how much your machine really runs
03
Calculate performance with OEE: How close are you to maximum output?
01.
To calculate the OEE formula—availability, performance, and quality—each factor must be measured over a defined time period and then multiplied together.
The result reflects the overall effectiveness of the manufacturing process.
OEE = Availability Factor × Performance Factor × Quality Factor
Example:
OEE = 90% x 95% x 98% = 83.8%
Use our Excel template to calculate your OEE, making it easy to uncover hidden potential in your production.
It’s worth examining each factor of the OEE metric individually to identify targeted opportunities for improvement.
02.
Determine availability with the OEE formula: This is how much your machine really runs
Availability indicates how long your equipment was actually producing during the planned production time.
To calculate this OEE factor, you’ll need the planned production time, the actual run time (i.e., when the machine was actually operating), and a detailed record of all machine downtimes.
Availability Factor =
Operating time
Schedule occupancy time
Downtimes are categorized as either planned (e.g., setup, material change, maintenance) or unplanned (e.g., machine failure, operator absence due to illness). Both result in availability losses.
💡 PRO TIP:
Planned downtimes are part of the production process but are often overlooked in OEE calculations. It is valuable to include them in the OEE calculation to compare setup times and help identify opportunities to optimize production schedules.
Unplanned downtimes, such as those caused by equipment failure, urgent maintenance, material jams, or operator absences due to illness, directly impact production and should always be considered in the OEE metric. Did you know: ENLYZE automatically detects downtimes and helps operators assign them to the correct cause categories.
Targeted improvement of machine availability
Analyze the most common causes of downtime—ideally using a Pareto Analysis. Focus on the largest single cause to develop a plan-of-action to resolve the issue and regularly track progress with the OEE formula.
Other factors that can influence equipment availability include:
Frequency of breakdowns and failures
Duration of maintenance and repair work
Quality of maintenance and repair work
Availability of spare parts
Qualifications and experience of personnel
Environmental conditions
Take action to optimize these factors, for example by reducing wait times for spare parts. This helps minimize bottlenecks while increasing manufacturing productivity.
💡 What is the Pareto analysis?
The Pareto Analysis is a method used to identify which causes are responsible for the majority of problems or outcomes.
It is based on the principle that about 20% of the causes account for 80% of the effect. The analysis helps set priorities by focusing on the most significant influencing factors—where a change will have the greatest impact.
Power factor =
Production time at maximum output
Actual runtime
03.
Calculate performance with OEE: How close are you to maximum output?
The formula for the performance factor in the OEE calculation is more complex than for availability and quality. It shows how much was actually produced compared to the maximum possible amount at optimal speed. For reliable values, you should monitor and regularly evaluate your manufacturing process.
The maximum production speed is referred to as the performance reference. It should be defined on a product-specific basis, because all products cannot be produced at the same speed. Using a uniform reference for all products will distort the performance factor and, consequently, the overall OEE value.
Correctly defining maximum performance
Traditionally, OEE performance has been assessed based on the amount produced per hour. Often, the original equipment manufacturer (OEM) specified nameplate capacity serves as the reference. But this is not product-specific and not very meaningful.
A modern machine data collection system, such as the one from ENLYZE, allows for precise OEE calculation. The programmable logic controller (PLC) continuously tracks production speed. From this, the current performance is calculated, and the product-specific performance reference is automatically determined. Our software identifies the Maximum Demonstrated Speed (MDS) for each product and uses it as the realistic performance reference.
Conclusion: Only a validated, product-specific maximum speed accurately reflects performance losses in OEE and reveals where you can make targeted improvements.
Uncovering and reducing performance losses
Performance losses often go unnoticed because they are not captured due to a lack of data. Only through continuous performance monitoring does it become clear how much production volume is lost. With automated OEE reports, these losses are made visible and can be analyzed in detail.
To improve performance, standardizing the setting parameters for each product is key. This allows you to reduce performance losses systematically and increase equipment efficiency. Tools like digital process guides can help ensure the optimal settings for each product and achieve significant performance improvements.
04.
Good output vs. scrap: Quality factor calculation with OEE
The third component in calculating OEE is the quality factor. It shows how much of the produced quantity can be used as a viable end product (good output) and not scrap. To calculate this, the good output is compared to the total output quantity.
The total quantity is derived from the raw material used or the sum of the good output and scrap. It can be automatically captured through machine data or recorded manually.
Quality factor =
Good quantity
Manufactured quantity
Identifying and improving causes of scrap
For tracking scrap we recommend a similar approach as with downtimes: every instance of scrap should be linked to a category or specific reason. A Pareto Analysis will help you identify the top causes of scrap.
Once you've identified and monitored the main causes, you can focus on continuous improvement.
Measure Overall Equipment Effectiveness (OEE) using the OEE formula
Once you have calculated availability, performance, and quality, you can easily calculate the OEE value using the OEE calculator in Excel or calculate the formula manually. This provides an overview of the optimization potential in your manufacturing process.
While manually calculating OEE is possible, it is time-consuming. A more efficient solution is OEE software that directly collects data from machines, connects it to order data and automatically analyzes OEE. This saves time and provides actionable insights, including key production KPIs in real-time.
A good OEE value is typically around 80%, while average values range between 60% and 70%. Since OEE is a relative metric, values can be artificially inflated—up to an unrealistic 100%—if reference points are set too low.
Comparing equipment or companies is not very meaningful, as processes, conditions, and measurement methods can vary significantly. As an internal metric, OEE shows where productivity is lost and provides a foundation for targeted optimization.
Analyze OEE over time Instead of setting a fixed target value
What matters is not the absolute value of Overall Equipment Effectiveness (OEE), but its development over time. This means that the goal should not be a fixed OEE target like, "We want to achieve an OEE of 85 percent!" but rather: "We want to increase OEE by 5 percentage points over the next 6 months compared to today."
OEE and Lean Manufacturing share the common goal of making processes more efficient. If you want to calculate OEE and perform a thorough process analysis, you can leverage Lean Principles. These principles help reduce waste and improve capacity utilization. At the same time, OEE provides transparency into manufacturing bottlenecks and reveals where failures occur, allowing for targeted actions to increase productivity.
In manufacturing, six typical types of losses occur that negatively affect Overall Equipment Effectiveness (OEE). They can be attributed to the three OEE factors: availability, performance, and quality. These losses should be systematically recorded and analyzed to enable targeted improvement measures.
Availability:
Planned downtimes: for example, setup processes, changes, or maintenance
Unplanned downtimes: such as material bottlenecks or faults
Performance:
Short stops: secondary downtimes – often unnoticed and usually irrelevant in continuous production
Reduced speed: system operates below the target performance
Quality:
Run-in scrap: scrap produced during the start-up of the system
Operational scrap: defective products due to process issues
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The manual calculation of OEE involves considerable effort. Often, the required data is available in different formats and systems, making their consolidation time-consuming and error-prone. To ensure OEE results you can trust, accurately capturing downtimes is key, as well as tracking performance deviations per product.
To ensure that the OEE analysis is reliable, the following points should be considered:
Consistent data collection: Manually or automated – the main thing is to be consistent and reliable.
Regular calculation: OEE as well as availability, performance, and quality should be continuously measured.
Systematic documentation of faults and scrap reasons: Only if you know the causes can you optimize or resolve them.
Open communication: OEE values should not be stored in isolation, but made accessible to all relevant stakeholders.
Leverage data depth: The more information you have available, the better causal relationships and optimization potential can be recognized.
When an OEE software calculates OEE automatically, deviations and impact of resolutions can be analyzed directly, and measures can be derived more quickly. This way, you can save time and focus on increasing productivity.
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