MTBF is a calculation used to predict the time between failures of a piece of machinery. Mean time between failures MTBF is a prediction of the time between the innate failures of a piece of machinery during normal operating hours. In other words, MTBF is a maintenance metric, represented in hours, showing how long a piece of equipment operates without interruption.
It's important to note that MTBF is only used for repairable items and as one tool to help plan for the inevitability of key equipment repair. Before you calculate MTBF, you need to understand how it affects reliability and availability.
Having high reliability and availability usually go together, but the terms are not interchangeable. Reliability is the ability of an asset or component to perform its required functions under certain conditions for a predetermined period of time. Put another way, it's the likelihood that a piece of machinery will do what it's meant to do with no failures. Think of an airplane; its mission is to safely complete a flight and get passengers to their destination with no catastrophic failures.
Availability is the time an asset or component is operational and accessible when it's needed for use. In other words, it's the likelihood that a piece of machinery is in a state to perform its intended function at any given time.
Availability is determined by the reliability of a system and its recovery time when a failure does occur. Availability is usually looked at in tandem with reliability because, once a failure occurs, the critical variable switches to getting the asset up and running as quickly as possible.
There are a few variations of MTBF you may encounter. You'll most likely see these variations when differentiating between critical and non-critical failures. MTBF is calculated by taking the total time an asset is running uptime and dividing it by the number of breakdowns that happened over that same period of time.
So, what does this tell us? In this example, the MTBF isn't suggesting that each widget should last hours. It's saying if you run a group of widgets, the average time between failures within the tested group is hours.
In other words, MTBF isn't meant to predict the behavior of a single component; it predicts the behavior of a group of components. It's important to understand that when defining "time," it may not always mean clock time; it could be the time in which the system is actually being used. For example, you may have a machine that has been run eight hours a day which might last three times as long as the exact same machine running 24 hours a day. The MTBF for both machines is the same because they both endured the same number of operating hours.
Let's look at another example of the MTBF calculation. Your team must act quickly — the sooner you respond to failures, the faster they will be solved. On one hand, decreasing MTTR depends on efficient real-time maintenance management and clear work orders ,.
On the other hand, you must understand why failures happen. Getting to the root cause of each failure is the only way to prevent it from happening again. Or, at least, to establish processes that make it less likely to occur again.
Coupling swift action with root cause analysis will avoid lengthy breakdowns. In this case, maintain best practices and never fail to invest in preventive maintenance! MTBF is helpful for buyers who want to make sure they get the most reliable product, fly the most reliable airplane, or choose the safest manufacturing equipment for their plant.
It can also help companies develop informed recommendations about when customers should replace a part, upgrade a system, or bring a product in for maintenance. MTBF is a metric for failures in repairable systems. For failures that require system replacement, typically people use the term MTTF mean time to failure.
For example, think of a car engine. MTTR mean time to repair is the average time it takes to repair a system usually technical or mechanical. It includes both the repair time and any testing time.
You can calculate MTTR by adding up the total time spent on repairs during any given period and then dividing that time by the number of repairs. In that time, there were 10 outages and systems were actively being repaired for four hours.
Four hours is minutes. Which means the mean time to repair in this case would be 24 minutes. Mean time to repair is not always the same amount of time as the system outage itself. In some cases, repairs start within minutes of a product failure or system outage. This metric is most useful when tracking how quickly maintenance staff is able to repair an issue. MTTR is a metric support and maintenance teams use to keep repairs on track.
The goal is to get this number as low as possible by increasing the efficiency of repair processes and teams. MTTR mean time to recovery or mean time to restore is the average time it takes to recover from a product or system failure. This includes the full time of the outage—from the time the system or product fails to the time that it becomes fully operational again.
Mean time to recovery is calculated by adding up all the downtime in a specific period and dividing it by the number of incidents. This MTTR is a measure of the speed of your full recovery process. Is it as quick as you want it to be? How does it compare to your competitors? This is a high-level metric that helps you identify if you have a problem. However, if you want to diagnose where the problem lies within your process is it an issue with your alerts system? Is the team taking too long on fixes?
Does it take too long for someone to respond to a fix request? The problem could be with your alert system. Is there a delay between a failure and an alert? Are alerts taking longer than they should to get to the right person? The problem could be with diagnostics. Are you able to figure out what the problem is quickly? Are there processes that could be improved? Or the problem could be with repairs. Are your maintenance teams as effective as they could be? MTTR mean time to resolve is the average time it takes to fully resolve a failure.
This metric extends the responsibility of the team handling the fix to improving performance long-term. To calculate this MTTR, add up the full resolution time during the period you want to track and divide by the number of incidents. Which means your MTTR is four hours.
MTTR is typically used when talking about unplanned incidents, not service requests which are typically planned. MTTR mean time to respond is the average time it takes to recover from a product or system failure from the time when you are first alerted to that failure. This does not include any lag time in your alert system. MTTF offers a reasonable indication of how long a product is expected to last until it fails. In other words, it provides an estimate of service life. MTTF is calculated by dividing the total hours of operation by the number of products being tracked — most MTTF data is collected by running multiple products often thousands over an extended period of time to provide the most accurate possible figure.
Availability measures both system running time and downtime.
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