In manufacturing operations, Overall Equipment Effectiveness, or OEE in short, is the gold standard for measuring productivity.
Overall Equipment Effectiveness is a simple but powerful metric that has been used for decades, although it gained mainstream popularity in the last decade or so. Since then, OEE has helped many teams and organizations visualize, monitor, and reduce inefficient usage of equipment and waste.
However, many people are still confused about the concept of OEE and about the terms "effectiveness" and "efficiency," and in this guide, we'll address these things in a clear and comprehensive way.
In this guide to OEE, you'll learn about:
And more.
Let us begin this guide with the basics: what is Overall Equipment Effectiveness?
Efficiency vs. Effectiveness
To really understand OEE, we have to make sure we understand the definition of "effectiveness" as opposed to "efficiency."
The two terms have often been used interchangeably, but although they are related, they aren't one and the same. Both terms essentially mean "capable of producing the desired result," however there is an important difference between the two:
For example, assume a piece of equipment can technically produce 1,000 products an hour but somehow only produces 800 items an hour. In this case, the equipment is 80% effective.
On the other hand, out of these 800 items, 200 (25%) are considered defective. In this case, the equipment is considered only 75% efficient.
Thus, a piece of equipment can be only 50% effective but 100% efficient, and vice versa; it can be 100% effective but only 50% efficient.
When calculating OEE, it's crucial to understand that we are discussing effectiveness instead of efficiency.
OEE is a measurement method used in Total Productive Maintenance (TPM) programs, which is a methodology designed to improve productivity in the workplace by ensuring all processes are more reliable and energy-efficient.
The main purpose of TPM is to maintain equipment so that it stays in optimal condition for as long as possible while minimizing issues and damages.
TPM implementation has three ideal objectives:
In the context of TPM, OEE is an important metric in TPM implementation that is useful as a baseline and a benchmark:
OEE is a standardized methodology to measure a piece of equipment's effectiveness during the defined operative mode or period in which all activities are related to production.
Measuring OEE essentially enables the organization and/or management to understand three things:
While considering these three key OEE elements, the formula for calculating OEE is as follows:
Overall Equipment Effectiveness= Availability x Performance x Quality
OEE is the primary indicator of a machine's performance. So for most manufacturing companies, it is beneficial to know, how to calculate OEE for multiple machines due to three main reasons:
By knowing your actual OEE and the ideal OEE score to pursue, you can determine the ideal performance of your equipment to ensure your business stays profitable. Set a lower OEE limit knowing that if you stay above this number, your production is profitable.
When your equipment's OEE score suddenly goes below its usual level and stays there, it's a sign that your machine needs maintenance and (probably) repairs.
A Low OEE score can help you troubleshoot your machine, identify potential issues, and figure out what needs to be done to bring back its optimal performance.
If your manufacturing company has multiple machines, then calculating OEE can help you identify which machine is currently underperforming so you can fix the issue and improve productivity.
Availability refers to how long (in a unit of time) a piece of equipment is available to operate, divided by the operative mode time (the total possible available time).
Availability takes breakdowns/unplanned downtime and planned downtime into account, including meetings, lunch breaks, and other regularly scheduled breaks.
Availability= B/A, in which:
A=Total operative mode time
B=Run time
A-B=downtime
Performance refers to how fast the piece of equipment runs while it is running within the operative mode time.
A 100% performance score means the process is running as fast as the machine is theoretically capable of running during the total available time.
Performance takes calculated speed loss into account, including human error, material mistakes, stuck material, etc.
Performance=D/C, in which:
C=Optimal operational speed
D=Actual speed
C-D=speed loss
Quality refers to the number of products that are within specification or requirement compared to the total number of products produced.
A 100% score in quality means there are 0 defects.
Quality=F/E, in which
E=Total products produced
F=Accepted products
E-F=product waste
Considering all these elements, we can use the following formula:
OEE = B/A x D/C x F/E
What is considered a good OEE score? Below is the commonly accepted benchmark:
Let's assume we have a machine that operates with the following details:
Based on this data, we can calculate:
Availability score = Run time/total operative mode time
= 10/12
=83.3%
Performance score = Actual speed/Optimal operational speed
=22,000/25,000
=88%
Quality score = Accepted products/total products produced
=21,000/22,000
=95.5%
Last but not least, we can finally calculate the OEE score of the machine:
OEE= Availability score x Performance score x Quality score
= 83.3% x 88% x 95.5%
=70%
Which is the same as 21,000/30,000=70%, but now we have a breakdown of the areas of loss to address.
In this example, the equipment has a typical OEE score with a pretty big room for improvement.
Once you've calculated OEE for your machine or multiple machines, how can you improve upon it?
OEE can be improved in many different ways: identifying and eliminating bottlenecks, improving maintenance schedules, developing better workflows, and so on. However, the actual answer would depend on the state of each piece of equipment and the specific effectiveness issues it is currently facing.
Below, we will discuss some actionable strategies you can use to improve OEE:
In practice, improving OEE on all assets can be time-consuming and not cost-effective, so you'll need to prioritize.
It's best to focus your resources and time on improving assets and equipment that are most mission-critical and, ideally, those that can help improve other assets up and down the value chain with the only effort directed on this single piece of equipment.
Another important strategy to improve OEE is to automate production data collection and reporting by implementing OEE data collection software.
The faster and the more immediate you gain access to production data, the faster you can identify bottlenecks and issues, and the faster you can troubleshoot the issues ASAP. Not only that, but manual data collection is both time-consuming and error-prone, which may contribute to lowering the OEE score.
Fortunately, thanks to advancements in technology and especially IoT (Internet of Things) implementations, it's much easier and more affordable to automate data collection, analytics, and data reporting processes.
The OEE score of each machine might seem simple, but in reality, understanding why the score is that way can be quite complex.
For example, it's possible that the low OEE of a machine happens due to an issue that happens much earlier in the production process caused by another machine, which can be quite difficult to identify in practice.
With that being said, it's recommended to use Root Cause Analysis (RCA) to help you understand the core cause of a problem and, in this case, the root cause of the OEE score.
RCA consists of six key steps:
Knowing and addressing the root cause of the OEE is the only viable solution instead of only treating symptoms. This can help you prevent the OEE losses from recurring in the future.
Another key strategy to improve the OEE of your machines is to make sure all production stops are properly addressed to create visibility of your production's downtime.
The basic approach you can take is to simply ask your supervisors to comment on each stop and check them at the end of each shift. The supervisors must aim to understand why each stop (especially unplanned ones) happens and add a comment on their report.
Ultimately, the goal is to develop a more thorough understanding of your production's downtime and how to prevent them from happening in the future.
Various negative conditions in the working environment can improve an equipment's OEE. Excess dust inside the machine, for example, can significantly affect equipment OEE. Poor lighting conditions may also affect factory workers in operating the machines, lowering OEE.
Identify potential issues in the working environment surrounding the machine that may affect OEE, and fix the issues accordingly.
In this post, you have learned about Overall Equipment Effectiveness (OEE), how to calculate OEE for a production line, as well as important strategies and best practices you can do to improve your machines' OEE.
It's important to remember that OEE scores of machines will vary at different times of operations and on different days depending on many different factors, so the manual calculation and monitoring of OEE is not recommended.
Instead, using visual factory software can help you monitor machine downtime and the OEE metrics of each production line in real-time, so you can more quickly and accurately calculate the OEE score.
Ultimately, keeping track of OEE for all machines can help you maintain and improve your business's performance both in qualitative and quantitative ways.