Mean time to failure (MTTF) is a maintenance key performance indicator (KPI) used to track the lifespan of assets that cannot be repaired and must be replaced outright. Knowing the lifespan of these assets allows your business to make strategic decisions regarding inventory, production, and maintenance to ensure maximum equipment uptime.
What is Mean Time to Failure (MTTF)?
MTTF measures the time between an asset’s installation and the point of failure. It tells you the average number of hours that each item, part, or component will last before it needs to be replaced.
MTTF is specifically used for assets that cannot be repaired. Typically, replacing these assets is less expensive and more efficient than fixing them.
As such, mean time to failure is a helpful calculation for smaller assets and individual components within larger machinery, such as:
- lightbulbs
- wheels
- conveyor rollers
- ball bearings
- fan belts
- transistors
Knowing a part’s mean time to failure gives maintenance teams a clearer understanding of the reliability of the parts that make up a larger production asset. It also gives them actionable insights to stay ahead of their maintenance needs.
Even though some individual components can’t be repaired, they are often part of a larger asset that is repairable. The longevity and reliability of these components can have a major impact on equipment uptime and the overall performance of larger assets.
Once maintenance teams know each component’s MTTF, they can use that number to manage their inventory and make smarter decisions about when to purchase parts. For example, in just-in-time manufacturing environments, MTTF metrics can be used to predict when to order parts so that they arrive as they are needed.
MTTF Helps Answer Important Maintenance Questions
Knowing how to calculate MTTF can help your team make strategic operation decisions. Even though mean time to failure is used for items that can’t be repaired, knowing mean time to failure for different items your business uses can help maximize uptime and save money.
We can also define mean time to failure as the average time to failure. While this isn’t a guarantee of how long each part will last, it is still helpful to know the average.
Here are a few important maintenance questions MTTF can help you answer:
Can Preventive Maintenance Extend the Asset’s Lifespan?
MTTF is best used for assets that are unable to be repaired. However, the lifespan of certain assets can still be extended by performing preventive maintenance. For example, lubricating ball bearings can help extend their useful life. You may also extend the useful life of other assets by using them according to the manufacturer’s recommendations.
Understanding mean time to failure can help you measure just how much preventive maintenance can extend the life of a particular part. With this information, maintenance teams can determine whether the value of conducting preventive maintenance on that part is worth the effort or if it is more time and cost effective to use a run-to-failure approach.
What is the Quality of the Available Replacement Parts?
The quality of replacement parts affects the overall lifespan of an asset, so choosing high-quality parts is key to extending the life of your equipment and ensuring overall efficiency. MTTF can indicate the quality of the replacement parts, so you can make better purchasing decisions when buying future replacement parts.
Part manufacturers may make decisions that impact the longevity and quality of the parts you’ve always used. When you know each item’s MTTF score and track it over time, you can see if the overall quality decreases. If it does, this could be an indication that it’s time to purchase parts from a different supplier.
When Should Replacement Parts be Ordered?
In addition to helping you decide what parts to purchase, MTTF can be used to decide when to best purchase replacement parts. Keeping an inventory of spare parts on hand is not always feasible due to space and cost constraints. Plus, some materials will deteriorate over time and cannot be stored long-term.
Maintenance teams can instead use MTTF to help them optimize parts ordering so that replacements arrive right before they are needed. A robust computerized maintenance management system (CMMS) can help optimize inventory by tracking what’s in stock and where it’s located, and anticipate supply chain lead time. A CMMS can track an item’s historical MTTF and also leverage it to manage inventory effectively.
How to Calculate MTTF
Calculating mean time to failure requires knowledge of the asset’s history. To calculate MTTF, you’ll need to know how many of that particular part were in use, as well as how long each individual part lasted. More specifically, you’ll have to calculate the number of hours each part was used between the initial installation and failure/replacement. The more data you have, the more accurate your MTTF calculation will be.
That’s why mean time to failure is best used for components that fail relatively quickly. Otherwise, it would take years to determine the MTTF score for longer-lasting equipment. It’s also important to keep in mind that MTTF should only be calculated between identical assets.
For example, if you’re calculating MTTF for light bulbs, be sure to use only lightbulbs with the same wattage. Differences in such variables lead to inaccurate, unusable results.
Mean Time to Failure Formula
An asset’s MTTF is calculated by dividing the total amount of operating hours by the number of specific assets in use.
You can use a calculator to find MTTF with this formula:
Total Operating Hours / Number of Assets = MTTF
Since operating hours are split between multiple assets, you’ll need to add up their total hours. For instance, if you were trying to calculate MTTF for a specific type of light bulb, you would need each bulb’s individual lifespan.
For example, say you have six bulbs — three with a lifespan of 1,000 hours and three with a lifespan of 1,200 hours. In total, the bulbs operate for 6,600 hours. Their MTTF calculation would look like:
6,600 total operating hours/ 6 light bulbs = 1,100 hours
So, each light bulb would have an MTTF of 1,100 hours.
MTTF vs MTBF and MTTR?
There are many different metrics that help measure maintenance effectiveness. MTTF is just one of these valuable snapshots into your operations and is fundamental to helping you track and respond to assets that can’t be repaired.
But what about repairable assets? There are a number of key metrics that you’ll need to consider. Two of the most important are mean time between failure (MTBF) and mean time to repair (MTTR).
MTBF depicts the expected time between two failures in a repairable system. Meanwhile, MTTR measures the average time to fix a failed asset, including the time it takes to test and diagnose.
What is the Difference Between MTBF and MTTF?
MTBF and MTTF are both useful metrics. They provide valuable information that your team can use to develop and iterate on maintenance procedures, ensuring continuous improvement in processes across your plant.
MTBF, or mean time between failures, is used for assets that can be repaired. This value tells you the average number of hours an asset can operate at best efforts before it needs maintenance. The length of time measured by MTBF is not the time between complete breakdowns. Instead, it’s the amount of time before the asset has to be repaired to operate optimally.
For example, if an asset is still operable but works slower than expected or allowed by your company’s best practices, it has reached failure since it needs to be repaired.
MTTF, or mean time to failure, is used for assets that need to be totally replaced. These assets may be completely irreparable, or they may simply take too much time and effort to repair, meaning your business will opt to replace them.
For example, you probably wouldn’t calculate MTTF for a repairable piece of manufacturing equipment with an estimated lifespan of 15 years. However, you would calculate mean time to failure for a fan belt that the manufacturing equipment requires to run optimally. This part may need to be replaced dozens of times over the asset’s useful lifespan.
While you wouldn’t calculate MTTF for larger assets, you would calculate mean time between failures. This would show you how often the equipment needs to be repaired and can give you useful information that will help your maintenance team make decisions about preventive maintenance. While the asset will probably need to be replaced eventually, it can be kept in good working order by repairing it as needed.
How and When to Use MTTF?
Tracking mean time to failure for common items like light bulbs and ball bearings can sound daunting. Calculating this metric correctly requires good record-keeping, which can translate to lots of paperwork or time spent tracking data in a digital spreadsheet.
However, a CMMS can help you automatically track these metrics. With the help of wirelessly connected sensors and smart software, a comprehensive CMMS like eMaint can generate reports on demand so that you have all the MTTF data you need at your fingertips.
Once you’ve calculated MTTF for certain parts, you can use it when:
- Making purchasing decisions: Knowing each part’s MTTF can help you decide where to order parts.
- Adjusting maintenance procedures: MTTF scores can help you decide whether to adjust maintenance procedures to increase MTTF for certain parts that may have extendable lifespans.
- Creating operations budgets: Knowing mean time to failure for each part can help you estimate how much you’ll spend on parts over a given period of time.
- Developing inventory strategy: When you know the average life of spare parts, you can decide whether you need to keep them on hand and how often you should order them.
KPIs and failure metrics like MTTF are key to measuring the success of maintenance programs. Manufacturing plants must be more productive than ever before to stay competitive. To keep up with ever-increasing demand, maintenance and reliability teams are overhauling their old practices and adopting new ones to minimize the impact of equipment failure on production timelines.
The past two decades have seen an increase in the use of remote condition monitoring technology to help predict and prevent unexpected failures. With access to more data about asset health, via power monitoring and vibration monitoring, maintenance teams can gain a clearer picture of their efficiency and the general condition of a manufacturing plant’s machinery.
A robust CMMS makes all of this information readily available, giving you the tools you need to optimize maintenance practices across your organization. If you’re in the market for an award-winning CMMS platform that can track MTTF and other KPIs, reach out to the experts at eMaint.