Want to get some information about MTBF (mean time between failure)? Now, you come to the right place. This post tells you what MTBF is and how to use it. Besides, you can also get some information about MTTR and MTTF from this post.

What Is MTBF

What is MTBF? MTBF is the abbreviation of the mean time between failure, which is the estimated elapsed time between inherent failures of mechanical or electronic systems during normal system operation. MTBF can be calculated as the arithmetic mean (average) time between system failures.

Tip: If you want to get more information about system failure, you can go to the MiniTool official website.

MTBF describes the expected time between two failures of a repairable system. For example, three identical systems begin to operate normally at time 0 until they all fail. The first system failed after 100 hours, the second system failed after 120 hours, and the third system failed after 130 hours.

The MTBF of the system is the average of these three failure times, which is 116.667 hours. If the system is not repairable, their MTTF will be 116.667 hours. To calculate MTBF, divide the total operating hours in a period by the number of failures that occurred during that period. MTBF is usually measured in hours.

MTBF = # of operational hours ÷ # of failures

What Is MTTR

MTTR (mean time to repair) refers to the time required to repair the system and restore it to full functionality. When the maintenance starts, the MTTR clock starts counting until the operation is resumed. This includes repair time, test cycles, and return to normal operation.

To calculate MTTR, divide the total maintenance time in a given period by the total number of maintenance operations.

MTTR can be used to inform maintenance decisions such as:

  • when to repair or replace assets
  • whether to lease or buy equipment
  • quantity of parts and inventory to have on hand

What Is MTTF

MTTF (mean time to failure) is a very basic measure of the reliability of non-repairable systems. It represents the length of time a project is expected to continue running until it fails. MTTF is calculated as total business hours divided by the total number of items to be tracked.

MTTF is referred to as the life cycle of any product or device. Its value is calculated by observing a large number of items of the same type for a long time and looking at their average failure time. MTTF is calculated as the total business hours divided by the total number of items to be tracked.

MTTF is an important indicator used to estimate the life of non-repairable products. Common examples of these products include products from fan belts in cars to light bulbs in our homes and offices.

How to Use MTBF

Now, let’s see how to use MTBF. MTBF is used to predict the probability of asset failure in a specific period or the frequency of occurrence of a certain type of failure. When used in conjunction with other maintenance strategies (such as failure code and root cause analysis) and other maintenance indicators (such as MTTR), it will help you avoid costly failures.

With this information, PM can be created more easily, so reliability can be improved by handling problems before they cause failures. You can not only locate faults for PM but also investigate why a certain problem causes the MTBF to decrease.

PM is not the only task that can be optimized using MTBF. By tracking this maintenance index, inventory management can also be improved. By knowing how long the equipment will be out of production, you can fine-tune your MRO inventory purchase method.

MTBF can help you make difficult decisions easier. Giving up a piece of equipment and buying an expensive new machine is never easy. However, if all attempts to lower the MTBF are unsuccessful, it may be in your best interest to replace the asset instead of spending time and money constantly to repair the asset.

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Final Words

To sum up, this post is mainly talking about MTBF (mean time between failure), and after reading this post, you can also know what MTTR and MTTF are and how to use MTBF. Now, here comes the end of this post.

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