Knowing how to calculate OEE performance can transform your manufacturing efficiency. It’s a key metric that every manufacturer should understand. In this guide, we’ll break down the process step-by-step, equipping you with the knowledge to improve your operations significantly.
What is Overall Equipment Effectiveness?
The concept of Overall Equipment Effectiveness (OEE) was first developed and introduced by Seiichi Nakajima in the 1960s as part of the Total Productive Maintenance (TPM) system. OEE is a key performance indicator measuring manufacturing productivity used to measure the efficiency and productivity of manufacturing equipment. The metric takes into account factors such as availability, performance, and quality to determine the overall effectiveness of a machine or process.
Key Takeaways From this Article:
- Overall Equipment Effectiveness is a key performance indicator used to measure the efficiency and productivity of manufacturing equipment.
- Takes into account factors such as availability, performance, and quality to determine the overall effectiveness of a machine or manufacturing process.
- Calculating can help businesses identify areas for improvement and make data-driven decisions to optimize their production processes.
- Total Effective Equipment Performance (TEEP) is another metric that can be used in conjunction with Overall Equipment Effectiveness to measure the overall effectiveness of production equipment.
How is OEE used?
It can be used to identify inefficiencies in production processes and make data-driven decisions to optimize operations. It can also be used to set performance targets and track improvements over time.
Why is Overall Equipment Effectiveness important?
As an important metric for manufacturers, Overall Equipment Effectiveness provides valuable insights into the efficiency of their operations. By measuring and tracking OEE, businesses can identify areas for improvement and make data-driven decisions to optimize their production processes. This can lead to lower costs, increased manufacturing productivity, and improved profitability.
How to Calculate OEE Performance?
OEE is usually expressed as a percentage, with higher percentages indicating better overall equipment performance. Calculating OEE involves taking into account three key factors: availability, performance, and quality.
Let’s break down each factor further:
Availability measures the amount of time a machine or process is available for production. It takes into account factors such as planned downtime, unplanned downtime, and changeover time.
Performance measures how well a machine or process is performing compared to its maximum possible speed.
Quality measures the number of good units produced compared to the total number of total units produced.
Simple OEE Calculation
In easy terms, Overall Equipment Effectiveness is the ratio of Fully Productive Time to Planned Production Time. In practice, it is calculated as follows:
OEE = (Good Count × Ideal Cycle Time) / Planned Production Time
While the given method of calculating OEE is completely valid, it doesn’t shed light on the three key factors contributing to losses: Availability, Performance, and Quality. To gain insights into quality loss in these three factors, we employ a more comprehensive calculation method.
The Preferred OEE Calculation
The preferred way on how to calculate OEE is based on the three OEE Factors: Availability, Performance, and Quality.
Availability
Availability considers all incidents that halt planned production for a significant amount of time, long enough to warrant recording a reason for the disruption. This typically means a pause in operations lasting several minutes or more.
Availability is calculated as the ratio of Run Time to Planned Production Time:
Availability = Run Time / Planned Production Time
Run Time is essentially the Planned Production Time minus the Stop Time. Here, Stop Time refers to any duration during which the manufacturing process, though intended to be operational, was not running. This could be due to unplanned stops, such as equipment failures or breakdowns, or planned stops like changeovers.
Run Time = Planned Production Time − Stop Time
Performance
Performance factors in any elements that cause the manufacturing or production process to operate at a speed less than its own maximum speed or potential when it’s in progress. This includes both Slow Cycles and minor interruptions, known as Small Stops.
Performance is the ratio of Net Run Time to Run Time and it’s calculated as:
Performance = (Ideal Cycle Time × Total Count) / Run Time
Ideal Cycle Time refers to the quickest cycle duration your manufacturing process can accomplish stable production, under optimal conditions. Consequently, when this is multiplied by the Total Count, it results in the Net Run Time, which represents production efficiency and the swiftest possible time to manufacture the components.
Since the rate is the reciprocal of time, Performance can also be calculated as:
Performance = (Total Count / Run Time) / Ideal Run Rate
Keep in mind that the top performance score should never be greater than 100%. If that’s the case, that usually indicates that Ideal Cycle Time is set incorrectly as it is too high.
Quality
Quality considers the manufactured parts that fail to meet the set quality standards, encompassing poor performance and those that require rework. It’s important to note that OEE Quality score is akin to First Pass Yield, as it designates ‘Good Parts’ as those that successfully navigate the manufacturing process on the first attempt, eliminating the need for any subsequent rework.
Quality is calculated as:
Quality = Good Count / Total Count
This is equivalent to calculating the proportion of Fully Productive Time (time spent manufacturing only Good Parts at the fastest possible rate without any interruption) about Net Run Time (the time used to manufacture all parts at the quickest possible speed without any stoppage).
Final OEE Formula
OEE considers all losses, yielding a metric of truly productive manufacturing time. It’s calculated as follows:
OEE = Availability × Performance × Quality
If the equations for Availability, Performance, and Quality are substituted, like already mentioned in the above, and the three components are reduced to their simplest terms, the result is again:
OEE = (Good Count × Ideal Cycle Time) / Planned Production Time
This is the “easiest” OEE calculation as already described earlier.
Why you Should use the Preferred OEE Calculation
OEE scores offer indispensable insights, painting a precise image of the efficiency of key components of your manufacturing process while facilitating easy tracking of improvements over time. However, what OEE score doesn’t reveal are the root causes of productivity losses. This is where Availability, Performance, and Quality come into play.
The preferred calculation provides a comprehensive view. It gives you one number that encapsulates your overall effectiveness, and three separate figures that identify the core characteristics of your performance losses (Availability, Performance, and Quality).
What is TEEP and how to calculate it?
Total Effective Equipment Performance, or TEEP, is another metric that can be used in conjunction with OEE to measure the overall effectiveness of a production line and equipment. TEEP takes into account all factors that affect equipment performance, including scheduled downtime, unscheduled downtime, and quality losses.
The formula for TEEP is as follows:
TEEP = (Total Run Time – Planned Downtime) / Total Run Time
What does OEE mean for Maintenance?
OEE is an important maintenance metric as it can help identify equipment issues, plan preventive maintenance, and optimize overall equipment performance. By tracking OEE, maintenance teams can proactively address potential problems before they lead to unplanned downtime or quality losses.
Overall Equipment Effectiveness is a powerful metric that allows businesses to continuously improve their operations and maximize productivity. By calculating and tracking OEE, manufacturers can identify areas for improvement, set performance targets, and make data-driven decisions to optimize their manufacturing processes further.
What You Should do Next
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