Mean Time Between Failures (MTBF)

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Mean time between failures or MTBF is a crucial maintenance metric to measure performance, safety, and equipment design, especially for critical or complex assets, like generators or airplanes. MTBF measures the operating hours between one failure and the next of an asset or component. It can be used with other maintenance strategies, like failure codes and root cause analysis, to avoid costly breakdowns. 

What is Mean Time Between Failures?

MTBF is also one-half of the formula used to calculate availability, together with the mean time to repair (MTTR). If a failure does occur, having all the data collected from mean time between failures can allow you to improve your maintenance strategy so that future failures are less likely to occur. Collecting data on MTBF is an important part of having a reliable and effective maintenance strategy.

The mean time between failures formula is a great way to see how well your company will perform in the long term. However, it doesn’t factor scheduled maintenance into its calculation. That can lead you astray if you plan on maintaining equipment over time or taking care of things yourself when they need attention most.

You can improve MTBF through careful design and by increasing the quality of components. 

Additionally, you can increase mean time between failures by reducing the number of opportunities for failure, such as by lowering the operating temperature of equipment or by providing better protection from vibration and shock. Improving MTBF is an important goal for any organization that relies on complex equipment.

How is MTBF Calculated?

MTBF (mean time between failures) measures how reliable an asset, part, or component is. You can calculate MTBF by dividing the total number of operational hours in a period by the number of failures that occurred in that period. Take this as an example: the functional lifetime for an asset is typically 1,000 hours per year. Over that year, that asset broke down eight times. As a result, the MTBF for that particular piece of equipment is 125 hours.

MTBF can be a useful metric for planning maintenance and repairing assets, but it’s important to keep in mind that it’s only an estimate. To obtain an accurate measure of MTBF, you must collect data from the actual performance of your equipment. Each asset operates under unique conditions and is impacted by human factors such as design, assembly, and maintenance, among others. As a result, you should avoid basing your maintenance on an MTBF estimate from a manual. By understanding the limitations of MTBF, you can use it to make more informed decisions about maintenance and repairs.

Is There a Way to Reduce the Impact of Failures?

MTBF can also help you move towards condition-based maintenance. Condition-based maintenance is a proactive approach that uses data to determine when you should perform maintenance. This allows you to optimize your maintenance schedule and prevent issues before they occur.

How Can Measuring Mean Time Between Failures Optimize Operations?

Making capital expenditure (CapEx) decisions can be tough, especially when it comes to replacing a piece of equipment that might be beyond repair. However, using mean time between failures (MTBF) data can help make these decisions a little easier. You can use mean time between failures to determine the cost of repair versus replacement and to create a business case for new equipment. If all efforts to combat low MTBF fail, it may be in your best interest to replace the asset rather than spending time and money repairing it all the time. Making CapEx decisions won’t be so tough when you have the data to back up your decision.

MTBF in a Nutshell

Improving mean time between failures and the reliability of your assets can have a huge impact on your organization, from the shop floor to the top floor. Calculating mean time between failures is one way to start conquering unplanned downtime at your facility. There are numerous reasons why an asset may fail. Taking inventory of the symptoms is the first step toward diagnosing and treating the problem. This is possible by tracking and analyzing MTBF. 

Asset reliability is important to businesses because unplanned downtime – even a few minutes – can cause production slowdowns, line stoppages, and delays in meeting customer demand. When something goes wrong, it often leads to other issues throughout the organization, impacting not just production but also sales, marketing, delivery, and more. Taking measures to improve mean time between failures can help businesses avoid these costly disruptions. Click here if you’d like to learn more about other common maintenance metrics.

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