How do you calculate the mean time between failures (MTBF) in incident response?

If you are an IT service provider, you know how important it is to measure and improve your incident response performance. One of the key metrics that can help you assess your reliability and availability is the mean time between failures (MTBF). But what exactly is MTBF and how do you calculate it? In this article, we will explain the concept of MTBF, its benefits and limitations, and the formula and steps to compute it.

1 What is MTBF?

MTBF stands for mean time between failures, and it is the average time that elapses between two consecutive failures of a system or component. A failure is any event that causes a system or component to stop functioning as expected or required. MTBF is usually expressed in hours, days, or years, depending on the context and the type of system or component. MTBF is a measure of reliability, as it indicates how often a system or component fails and how long it can operate without interruption.

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Tom Roltsch

Certified Reliability Engineer
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MTBF is used for repairable systems or components. It is the reciprocal of the Rate of Occurrence of Failures (ROCOF) and generally refers to a constant ROCOF or exponentially distributed failure interarrival times. If the ROCOF is time dependent, then MTBF is not generally used but instantaneous MTBF can be used instead. MTBF is used to calculate the probability of failures occurring in a time interval. The MTBF is the expected value, or most likely number of failures in the time interval.

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2 Why is MTBF important?

MTBF is important because it can help you evaluate and compare the reliability and availability of different systems or components. For example, if you have two servers that provide the same service, and one has a higher MTBF than the other, it means that the first server is more reliable and less likely to fail. This can help you decide which server to use or prioritize for maintenance. MTBF can also help you estimate the expected downtime and the frequency of repairs or replacements for a system or component. This can help you plan and budget your resources and minimize the impact of failures on your customers and users.

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Tom Roltsch

Certified Reliability Engineer
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In my work MTBF is important for two reasons. 1) it is easy to test, 2) it has the same denominator as mean time to repair (MTTR) thus MTBF and MTTR can be added together and if one divides MTBF by MTBF + MTTR the result is mean uptime/mean downtime which gives the mean availability or what is often called operational availability. However other factors can affect operational availability as well such as preventive maintenance and mean logistics delay time (MLDT).

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3 What are the limitations of MTBF?

MTBF is not a perfect metric, and it has some limitations that you should be aware of. First, MTBF does not account for the severity or impact of failures, only their frequency. For example, a system or component may have a high MTBF, but when it fails, it may cause a major disruption or damage. Second, MTBF does not account for the time or effort required to repair or restore a system or component, only the time between failures. For example, a system or component may have a low MTBF, but when it fails, it may be easy and quick to fix. Third, MTBF does not account for the variation or distribution of failures, only their average. For example, a system or component may have a high MTBF, but the actual time between failures may vary widely, making it unpredictable and unreliable.

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Tom Roltsch

Certified Reliability Engineer
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The limitation of using MTBF is that a constant ROCOF must be assumed (exponential distribution). Many repairable systems do not have a constant ROCOF. However, for a quick and easy test, the assumption of a constant ROCOF gives a ballpark estimate of reliability.

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4 How do you calculate MTBF?

To calculate MTBF, you need two pieces of information: the total operating time of a system or component, and the number of failures that occurred during that time. The formula for MTBF is: MTBF = Total operating time / Number of failures For example, if a server was operating for 10,000 hours and experienced 20 failures during that time, the MTBF would be: MTBF = 10,000 / 20 = 500 hours This means that on average, the server failed every 500 hours of operation.

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Tom Roltsch

Certified Reliability Engineer
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MTBF is a long term mean value but any test of MTBF will be for a finite time period, thus the sample estimate (also called point estimate) for MTBF must be evaluated using a confidence interval. The Chi-square distribution is used as a pivot to create an exact confidence interval for MTBF.

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5 How do you collect data for MTBF?

To collect data for MTBF, you need to track and record the operating time and the failures of your system or component. Logs and reports can be used to record the start and end time of each failure, as well as the total operating time during a given period. Additionally, monitoring and alerting tools can detect and notify you of any failures or anomalies in your system or component, allowing you to measure the duration and frequency of each failure. Tickets and incidents can also be used to document and manage the failures and their resolutions, as well as track the root causes and impacts of each failure.

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6 How do you improve MTBF?

To improve MTBF, you need to identify and reduce or eliminate the sources of failures in your system or component. Root cause analysis can help you discover the underlying causes of a failure, and take corrective and preventive actions. Reliability engineering can be used to design and test your system or component to meet the desired reliability and availability requirements. Maintenance and improvement activities should be used to inspect and repair your system or component regularly, as well as updating and upgrading it as needed. This will help keep it in good condition, while also enhancing its functionality and security.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How do you calculate the mean time between failures (MTBF) in incident response?

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1 What is MTBF?

2 Why is MTBF important?

3 What are the limitations of MTBF?

4 How do you calculate MTBF?

5 How do you collect data for MTBF?

6 How do you improve MTBF?

7 Here’s what else to consider

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