Which is right for you? OEE vs. MTBF

Measuring the performance and quality of your assets.

If you have had some exposure to the common thinking on this topic, then you are likely familiar with the terms OEE (Overall Equipment Effectiveness) and MTBF (Mean Time Between Failure). Both metrics can be very informative and drive specific behaviors when applied correctly. When applied incorrectly they can lead to confusion and frustration. In this post, I hope to shed some light on which of these measures may be more meaningful for your organization.

Let’s start with Overall Equipment Effectiveness.

Overall Equipment Effectiveness (OEE)

The layman’s version of OEE is simply defined as what percentage of the time that you could run good product at full capacity and with acceptable quality did you do so? In other words, the percentage of manufacturing time that is truly productive.

Perfection at OEE is 100%. Perfection means that you are running as fast as possible during planned production time with no defects. Anything more than that and you are breaking a few of the basic laws of physics, but we will save that discussion for another time.

The common OEE formula is as follows:
  • OEE = Overall Equipment Effectiveness
  • A = Availability = The percentage of the time that you ran and produced something.
  • P = Performance Efficiency = During the time that your process is running, at what percentage of your rated capacity (speed, throughput, etc.) did you run.
  • Q = Quality Rate = For all the units that you produced, what percentage of them were acceptable for sale to the customer, meeting the stated quality requirements.
For example:
  • Availability = 80%
  • Performance Efficiency = 90%
  • Quality Rate = 99%
  • OEE = 80% X 90% X 99%
  • OEE = 71.28%
OEE is a fantastic measure for a few important reasons:
  • Nowhere in the definition do the words “maintenance” or “operations” appear. It brings us together under one common measure. It facilitates two teams who can easily work at cross-purposes together. For example, availability losses can be experienced because of both maintenance and operating practices.
  • It forces us to focus on the loss of potential rather than what we have accomplished with no idea of what might be possible.
  • It brings together three aspects that are critical to meeting our customer’s needs. For example, if we only measured availability, we might overlook the fact that we ran at reduced speed.
  • It provides insights into how to improve your manufacturing process.

OEE is a bit of a universal metric and measuring it is a manufacturing best practice. It includes many of the critical aspects of your performance into a single metric. If you include some safety and cost measures, you are approaching a well-formed maintenance scorecard.

Mean Time Between Failure (MTBF)

Mean Time Between Failure tells us how often, on average (mean), we should expect to see an asset fail to fulfill its function. Higher MTBF performance is always considered to be better, as it indicates that your asset performs its intended function longer without any interruption attributed to failures. Downtime that may exist associated with planned maintenance activities is excluded from this calculation.

A simple definition for MTBF is:

MTBF = Operating Hours ÷ Number of Failures
  • Operating Hours = The time frame (frequency of measurement).
  • Number of Failures = The number of occurrences where the asset failed to fulfill its function.

Note: MTBF is the reciprocal of the Failure Rate (1/MTBF = Failure Rate).

For example:

Assume we measure MTBF monthly (30 days or 720 hours), and we have experienced 10 failures in this time frame.

  • MTBF = 720 hours ÷ 10 failures = 72 hours
  • MTBF = 30 days ÷ 10 failures = 3 days

This means that under current conditions, we should expect to experience a failure (loss of function) every 72 hours.

MTBF is a relative measure. Measuring MTBF on a highly critical asset or group of assets can be very meaningful. Measuring MTBF across an entire department or facility provides less value.

It is also important to note that MTBF does not consider situations where assets are running at a reduced rate, nor does it consider the size and duration of the event (not all equipment failures are equal – some are longer and have a greater impact than others).

Which is right for you? OEE or MTBF?

My short answer to this question is that if you can measure OEE in a meaningful way, then this is the metric for you. It covers many of the bases. Sadly, OEE does not fit in all situations.

Discrete Manufacturing

Discrete manufacturing is the production of distinct items. Automobiles, furniture, toys, smartphones, and airplanes are examples of discrete manufacturing products. You can easily identify a single item produced by discrete manufacturing.

If this definition fits, then OEE is for you. You should be concerned about factors such as availability, performance efficiency, and quality rate. These factors are central to your success.

Curious what world-class OEE looks like? Leanproduction.com defines world-class OEE at 85% (see their image below).

OEE benchmark scores; source leanproduction.com

Process Industries

Process industries are those that run a continuous batch where the distinction between one unit and another is not easily identified. Power generation, oil production, transport, and refining, as well as many petrochemical processes, fall into this category.

Unfortunately, in these types of environments, OEE might not serve our purposes for the following reasons:

  • Availability is often so critical in process industries that we see a high level of redundant equipment (with a corresponding capital investment). If we experience a failure of one piece of equipment, we switch over to the redundant unit and continue. For this reason, big losses in availability are usually greatly minimized.
  • Performance efficiency losses can exist, but rather than run slow, we often immediately bring the backup unit online and begin a fix to the underperforming unit.
  • It is often difficult, if not impossible, to identify quality losses in process industries. What does a bad kilowatt look like?

In these situations, establishing MTBF as a meaningful measure on specific highly critical assets and trending your performance upward will likely provide much more value than OEE.


Metrics are a funny thing. When used correctly and with the right application, they can provide a lot of value and focus to an organization. Used incorrectly, they tend to cause more harm than good.

When selecting the best metrics for your team, consider the following advice:

  • Keep it simple. Too many measures cloud the focus.
  • Make sure we know what actions to take to improve the performance of each metric. What must we do differently to improve? It sounds obvious, but surprisingly it is often overlooked.
  • Talk about it often. A metric is only as good as the leader who draws the team together to own it and acts on it.

Allied Reliability provides asset management consulting and predictive maintenance solutions across the lifecycle of your production assets to deliver required throughput at lowest operating cost while managing asset risk and achieving environment, social, and governance objectives. We do this by partnering with our clients and applying our proven asset management methodology and leveraging decades of practitioner experience across more verticals than any other provider. Our asset performance management solutions include Consulting & Training, Condition-based Maintenance, Industrial Staffing, Electrical Services, and Machine Reliability.

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