How to Calculate Overall Equipment Effectiveness (OEE)

No one intends for equipment to break down, have unplanned stops or face issues that affect good product quality, but the reality of manufacturing is that hitting full productivity isn’t always possible. Sometimes your conveyor belt has unexpected issues that hamper efficiency, but the more you monitor this, the more likely you are to limit productivity drains.

In particular, calculating overall equipment effectiveness (OEE) can go a long way toward improving your manufacturing operations. The more efficient your assets are, the better quality products your company can produce and sell, and the better return on investment you can get from your equipment.

Here, we’ll take a closer look at what calculating OEE entails and how it can help your company’s manufacturing performance.

3 Factors That Determine OEE Score

OEE is a lean manufacturing metric or key performance indicator (KPI) that facilities teams, operations managers, chief financial officers and others use to assess equipment efficiency. While some productivity measures assess areas like output per employee hours, OEE looks at whether you’re reaching your manufacturing productivity potential, based on the equipment you currently have.

This assessment is based on three factors:

• Availability: What percentage of manufacturing time is equipment available
• Performance: What percentage of a machine’s maximum output is equipment hitting
• Quality: What percentage of outputs are up to par

By looking at all three together, you can calculate an OEE percentage, and the closer you are to 100 percent, the closer you are to maximizing productivity based on your current assets.

OEE Formula, Defined 

In some ways, calculating OEE is straightforward, in the sense that you multiply the percentages for availability, performance and quality to get the overall efficiency percentage. However, you might not have these underlying percentages readily available, so it’s important to understand what goes into each of these key parts of the OEE calculation:

• Availability: Availability is calculated by dividing the total runtime of an asset by the total planned production time of an asset — meaning that excludes preventive maintenance and other scheduled time or planned stops accounted for in the planned production time. If you have machinery that’s used to pack orders 10 hours a day, five days a week, the total runtime would be 50 hours. Yet, if one day the equipment broke down and you lost five hours of runtime, that would mean the machinery was only available for 45 out of 50 possible hours, which equates to a 90 percent availability (or a 10 percent availability loss).
• Performance: Performance is calculated by dividing the actual system throughput by its maximum possible throughput. Suppose a beverage company has machinery that could package 1,000 cases of soda per hour — or 50,000 cases in the 50 hours per week that the system is supposed to run. Perhaps the machinery doesn’t fully break down, so the availability remains 50 hours that week, but an unidentified issue with a conveyor belt causes production line output to slow down, to the point where you only package 40,000 cases that week. In that case, the performance would be 80 percent (essentially a speed loss of 20 percent).
• Quality: The last component of OEE, quality, is calculated by dividing the number of usable units produced by the total units started. So, if the same packaging machinery puts out 40,000 cases in a given week, yet only 20,000 are usable because the machine was repaired incorrectly during the outage, causing labels to print upside down, then the quality would only be 50 percent.

Altogether, the 50 percent quality rate multiplied by 80 percent performance and 90 percent availability equals an OEE score of 36 percent. In other words, the machinery was only 36 percent effective that week.

Here’s a more precise visualization:

• Availability x Performance x Quality = OEE
• .50 x .80 x .90 = .36

In this example, the 50 percent quality rate was a huge drag on the total production efficiency. If that output error never occurred, and quality was 100 percent, while performance was 80 percent and availability was 90 percent, then OEE jumps to 72 percent — still room for improvement, but an acceptable score for many companies.

How OEE Works for Maintenance 

OEE scores provide crucial insights for maintenance teams. Each factor tells a story of what worked and didn’t work well from a maintenance perspective. 

Availability shows how often an asset runs or how often it’s being worked on outside of planned downtime. If your availability score is consistently low, that could be a clue that you’re having too much unplanned or emergency maintenance and need to have a more proactive maintenance approach.

The performance score can indicate whether or not your preventive maintenance schedule is sufficient enough. If you’re running scheduled inspections yet machines keep running into issues like overheating or clogs that hamper output, that might tell you that you need more frequent inspections or need to add technologies like sensors for predictive maintenance. 

Lastly, the quality score indicates whether maintenance is not only being performed enough but whether it’s being performed well. A poor quality score means there’s a lack of standardization across maintenance processes, as perhaps some inspections miss the mark, causing machines to have slow cycles below expected outputs. 

Together, the OEE score can help facilities and maintenance teams benchmark their overall ability to keep equipment running smoothly. Investing in an OEE improvement, such as through more scheduled maintenance, can lead to an improvement in the bottom line in that continuous improvement and more operating time equals increased revenue potential.

How to Improve OEE 

To improve your OEE, it’s important to first set your benchmark. A 100 percent OEE score is considered perfect, and while that might be your stretch goal, a more realistic target might be 85 percent, which is typically considered a good OEE score. Meanwhile, 60 percent is generally average and 40 percent is low, though this can vary by sector.

From there, you can dig into the three OEE measurement factors and identify areas for improvement. For example, low scores across all three areas could indicate a need for more preventive maintenance to improve equipment uptime and performance. You can experiment with how adjusting maintenance schedules and technologies affects OEE scores.

You also might find that OEE score improvement requires staff training. Equipment performance issues could be due to employee errors, either from an operational standpoint, or maintenance staff might need more training to perform repairs properly. Another possibility is that low scores indicate equipment is outdated and needs to be upgraded. Improving your OEE score can take a bit of trial and error, but by tracking it, you can see what works well and what doesn’t.

You can also look at OEE over different timescales. Daily OEE could be useful for those engaging in real-time maintenance, such as if you’re using Internet of Things (IoT) sensors to catch slowdowns or small stops almost immediately before they really start to hamper performance.

Meanwhile, monthly OEE scores could help maintenance teams determine if they’re meeting overall expectations and inspire strategic changes. For example, if OEE scores remain low, even after investing in more maintenance staff and technologies, that could indicate necessary changes, such as to quality control, to reduce output errors and breakdowns. 

Example of Using OEE 

An OEE score isn’t a vanity project. A high score might tell you you’re on the right track, while a low score indicates a need for improvement, but either way, it’s important to monitor these scores to ensure you’re getting the most out of your assets.

But what does using an OEE score look like in practicality? Consider Cargill, a large corporation whose business includes poultry processing plants. The company was noticing inefficiencies in the manufacturing process due to equipment issues, so it started collecting availability, performance and quality data to calculate OEE scores. From this data collection, Cargill realized that equipment failures were causing too much unplanned downtime, which slowed production speed and created a quality loss by letting too much food go to waste.

So, the company set goals to reduce downtime and optimize production speeds by scheduling more frequent maintenance, therefore improving output and quality as well as eliminating waste. But this wasn’t a one-time adjustment that the company had to rework. Cargill continued monitoring equipment and calculating OEE scores to refine their processes and discover ways to adjust maintenance so that the total available time of its key assets improved, ensuring they were working at their maximum speed.

How Coast Can Help With OEE 

Calculating OEE can point you toward areas of improvement, but implementing changes that lead you to higher OEE scores often requires more systematic adjustments. To make those changes, you need the right tools to keep everything in the production process organized and accountable.

In particular, using computerized maintenance management system (CMMS) software like Coast provides a centralized, streamlined way to collect asset data so you can track OEE and implement improvement plans. Coast also makes it easy to schedule preventive maintenance and track work orders so you can reduce unplanned downtime and get back to running at optimal capacity when emergency maintenance occurs.

See for yourself how Coast’s CMMS can help you improve maintenance and overall productivity. Sign up for a free account today.