WHAT IS OVERALL EQUIPMENT EFFECTIVENESS?
What is OEE?
OEE (Overall Equipment Effectiveness) is a simple way to understand how effectively a production operation is running compared to its full potential. It combines three factors—Availability, Performance, and Quality—into one score that shows how much productive time you’re actually getting from the time you planned to run.
Instead of guessing where time is being lost, OEE highlights which issues have the biggest impact on output, consistency, and overall efficiency.
Why OEE Matters
OEE reveals the gap between how your operation ran and how well it could have run under ideal conditions. That gap represents opportunities to produce more, reduce waste, and improve reliability.
Manufacturers use OEE to:
- Identify where production time is being lost
- Understand why output is lower than expected
- Measure how much product is made right the first time
- Prioritize improvement efforts based on real impact
- Create a baseline for consistent, repeatable performance
Whether you’re focused on throughput, quality, or minimizing downtime, OEE provides a clear, structured way to drive improvement.
The Three Parts of OEE
OEE is built from three factors that each measure a different type of production loss. Together, they show how much of your planned production time resulted in good output at the expected rate.
Availability
How often production is actually running when it was scheduled to run. This includes planned events (like changeovers) and unplanned ones (like stoppages or failures).
Performance
How efficiently the operation runs while it’s running. This accounts for slow cycles, micro-stops, or anything that prevents production from reaching ideal speed.
Quality
How much output meets defined quality standards on the first pass. It focuses on scrap, rework, and other losses that reduce usable product.
OEE Availability
OEE Availability shows how much of your scheduled production time was actually spent running. Planned production time excludes breaks, lunches, meetings, and other pre-arranged periods when the line or process is expected to be down. Any unplanned stop during planned production time lowers Availability.
Example:
If a line is scheduled for an 8-hour shift with two 15-minute breaks and one 30-minute lunch, the planned production time is 7 hours
(8 hours − 15 minutes − 15 minutes − 30 minutes).
During the production run, assume there are 25 downtime events totaling 45 minutes.
This reduces actual runtime to 6 hours and 15 minutes.
Availability is then:
6 hours 15 minutes ÷ 7 hours = 89%
OEE Performance
OEE Performance shows how efficiently the operation ran compared to its ideal running speed. The standard rate represents the maximum rate the line or work cell is designed to achieve. Performance is not based on how many units were produced overall, but rather how many units should have been processed during the time the operation was running. Any slow cycles, micro-stops, or inefficiencies during runtime reduce the Performance score.
Example:
If a work cell is designed to process 10 units per minute, then in a given amount of runtime we can calculate how many units it could theoretically process.
Using the 6 hours and 15 minutes (375 minutes) of actual runtime from the previous example:
375 minutes × 10 units per minute = 3,750 units (theoretical units started)
If the actual number of units processed is 3,000, then:
Performance = 3,000 ÷ 3,750 = 80%
OEE Quality
OEE Quality shows the percentage of produced units that meet quality standards on the first pass. Any units that require rework or are rejected outright reduce the Quality score. Because OEE focuses on first-pass yield, even small amounts of scrap or rework have a direct impact on this factor.
Example:
Using the earlier example where 3,000 units were processed, if 200 units are rejected during inspection, then 2,800 units are considered good.
Quality is calculated as:
2,800 ÷ 3,000 = 93%
Excited to learn more? Reach out to us to schedule a live demo today!
OEE Calculation
This final calculation combines all three OEE factors into a single measure of overall effectiveness. Each factor—Availability, Performance, and Quality—reflects a different type of loss, and they are independent of one another. If production stops unexpectedly, only Availability decreases. If the line runs slower than ideal, only Performance is affected. If units fail inspection, only Quality goes down. Together, these factors provide a complete view of how effectively planned production time was used.
Example:
Using the numbers from the earlier examples:
89% × 80% × 93% = 66% OEE
Interpreting the Result:
A 66% OEE may seem low at first glance, but it is important to remember that OEE is not intended to be compared to 100%. Instead, OEE is most meaningful when used to compare one production run to another or evaluate trends over time.
OEE as Part of a Larger Improvement Strategy
OEE is most effective when paired with real production context. It’s not just a score, but a lens for understanding why losses occur so teams can take action.
It helps you:
- Expose bottlenecks
- Reduce unplanned downtime
- Improve cycle consistency
- Standardize reporting across teams
- Align operations, engineering, and quality around shared goals
OEE supports continuous improvement by turning day-to-day production activity into clear, actionable insights.
Summary
OEE measures how effectively a production operation runs by combining Availability, Performance, and Quality into a single score. It gives manufacturers a clear view of where time is being lost and how much value they’re getting from their planned production time. With that clarity, teams can make targeted improvements that strengthen reliability, increase output, and support long-term success.
With Sepasoft’s OEE Downtime Module, you can compare OEE results across equipment, departments, facilities, operators, shifts, products, or any factor you choose to track (such as raw material vendor or environmental conditions). This allows you to identify patterns, understand the root causes of losses, and target improvements where they matter most. Request a demo to learn more.