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. Let's say you have a bottling machine designed to operate for 12 hours a day. The bottling machine breaks down after operating normally for 10 days. The MTBF in this example is hours. The MTBF calculation requires more steps when you have longer periods of time with increasing occurrences of failures.
For example, say the bottling machine that operates for 12 hours a day fails twice in 10 days. The first failure occurred 20 hours from the start time and took two hours to repair. The second failure happened 60 hours from the start time and took three hours to repair. Calculating the total uptime for the MTBF equation requires adding 20 initial uptime period , 18 start of first downtime period minus end of first downtime period and 57 hours start of second downtime period minus end of downtime period.
Over the useful life of an asset, the MTTR tends to move up because older assets take more time to repair. Their failures tend to be more serious. But this is the opposite of what you want, which is to find ways to reduce equipment downtime. By looking at the changes to its MTTR over time, the front office can better decide when an asset needs to be replaced or if it makes more sense to keep asking the maintenance department to repair it.
The front office can also use MTTR to make better decisions about which new assets to buy. One growing trend for assets is modular design. Imagine you have to fix one tiny spring in an old wristwatch. Just think of how carefully you would need to take the watch apart, replace that one broken piece, and then put everything back together.
It's a nightmare. But if that same watch had a more modular design, when you opened it up, there would be only three "pieces. This metric reveals reliability. It shows you how long on average an asset can run before you need to repair it. You need three things: the total number of hours the asset was in operation, the number of times it failed, and the amount of time it took to repair after each failure. You take the total number of hours of operation and divide it by the total number of failures.
Let's look at a simple example. Say you have a press that ran for 24 hours. During that time, it failed twice, and each time it took an hour to get it back up and running. So, it was in operation for a total of 22 hours 24 hours minus the two hours it took for repairs. Twenty-two divided by two, the total number of failures, equals Not a great asset.
On average it's going to fail every 11 hours. That's not good. But don't throw that press out just yet. Generally, when you have a low MTBF, you can trace it back to either operator error or issues with how the asset is being maintained and repaired. In some cases, what you need is more and better standardization across inspections, maintenance, and repairs. Instead, what you need is a way to get everyone following best practices. The benefits are twofold. First, the maintenance department can better look after assets and equipment when everyone is doing the best possible work.
Is it the product? Is it the procedure? But if everyone on the team checks the same way, adds the same product using the same process, you have very variables the check.
Not only does MTBF expose issues with past use and repairs, but it also helps set up your preventive maintenance schedule for the future. If you know an asset, on average, fails every hours, you can set PMs at every 90 hours. That way, you're getting the most bang for your PM buck. Here again, we're looking at reliability, but now it's for things you can't repair.
You can only replace them. The easiest example is light bulbs. When we looked at MTBF, all the numbers were from one asset. But for MTTF, we need a group of identical failed items.
Going back to our basic example, light bulbs, we might have four burnt-out bulbs, and they ran for 20, 22, 26, and 18 hours respectively. We add up those numbers and get When we divide that by the number of bulbs, which was four, we get an MTTF of Looking at our MTTF for the light bulbs, we can see right away you're going to need to switch brands, which is really all you can ever do when you have a low MTTF.
You can only improve your results by buying better quality products. Mean TTF is the "you get what you pay for" metric. MTTF also helps you better manage inventory. If you decide to stay with these awful light bulbs, at least you'll know to keep a lot of them in onsite inventory.
Later, if you decide to switch to a better bulb, you know you can reduce carrying costs by keeping fewer of them around. But sometimes the real power of MTTF is what it can tell you about the reliability of bigger, more complex assets. In fact, the MTTF for a small part inside a large asset can have a huge effect on that asset's reliability. Think about your car.
What happens when one of the interior lights burns out? Aside from some minor inconvenience, nothing.
But what about the fan belt? Like the light, it falls under the MTTF metric because it can't be fixed, only replaced. You can only really start to use failure metrics once you have a rock-solid data-collection system in place. Luckily, the easiest way to do that is with equipment maintenance software or work order software. If you don't have a CMMS yet, now's the perfect time to look into getting one. Simply it can be said the productive operational hours of a system without considering the failure duration.
Step 2: Note down the value of F. It is the number of failures occurred in a system. It is very important in Hardware product Industries rather than consumers. It is simply the number of failures occurring per hour.
Consumers mostly go with a price-driven approach hence do not mind much about MTBF. When it comes to industries, based on MTBF values only systems with different designs are compared. This value tells about Reliability, stability, and performance of a system. How often it gets a failure and how productive it is. Low MTBF always denotes that the system is not stable and not much operational. And for critical products such as Airplanes, safety equipment assets, inverters, generators, etc.
In this case, MTBF is the indicator of Performance expected from a specific system and also a metric for reliability and acts as a tool at the stage of design and production of hardware. This metric is simply known as average life expectancy. This says how often a product to be maintained to avoid breakdowns. An also MTBF is a current status indicator of performance in plant maintenance as a preventive maintenance schedule.
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