What is Mean Time to Failure (MTTF)?
Mean Time to Failure (MTTF) is a maintenance key performance indicator (KPI) used to track the lifespan of assets that cannot be repaired and therefore must be replaced. Knowing the lifespan of these assets allows your business to make strategic decisions regarding inventory, production, and maintenance to ensure maximum equipment uptime.
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 MTTF 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, so they can stay ahead of their maintenance needs.
Even though some individual components can’t be repaired, they are often part of a larger repairable asset. 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 they arrive as they are needed.
How Do You Calculate MTTF?
Calculating MTTF requires knowledge of the asset’s history. 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 MTTF is best used for components that fail relatively quickly. Otherwise, it would take years to determine the MTTF score for more durable 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 light bulbs with the same wattage. Differences in such variables lead to inaccurate, unusable results.
Here’s how to calculate MTTF with its unique formula.
Mean Time to Failure Formula (MTTF Formula)
An asset’s MTTF is calculated by dividing the total operating hours by the number of specific assets in use.
You can calculate it using the formula for MTTF:
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 lifespan.
Example of Mean Time to Failure Calculation
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.
Should MTTF Be High or Low?
Since MTTF is the mean number of hours until the point of failure, a high MTTF is better. This means your asset will last longer before failing.
A low MTTF indicates that your asset is likely to fail sooner, relative to an asset with a high MTTF. So, when you seek to “improve MTTF,” you’d aim for a higher number. However, it’s important to remember that each asset will have its own MTTF. For example, a high MTTF for a bearing may be 4,000 hours, while an MTTF of 4,000 hours for a conveyor belt may be unacceptably low. It all depends on the assets and their applications.
What Is a Good MTTF?
After you’ve entered your figures into the MTTF calculation, how do you determine if it’s a good MTTF for the asset? While there isn’t a universal answer to this question, maintenance teams may consider several factors to find out if they are achieving a good MTTF.
- Expected lifecycle: Compare your MTTF to the expected lifecycle of the component, either the one provided by the manufacturer or based on your own historical data. If your MTTF is longer, that means your components are lasting longer than expected and you’re getting a “good” MTTF. However, if your MTTF is shorter than expected, it may indicate you need to adjust your maintenance practices or purchase parts from a new supplier.
- Operational environment: The asset’s use environment can impact MTTF. A good MTTF for an asset operating in a harsh environment could be shorter than industry standards, but it could still be good when considered in its entire context. For example, ball bearings operated in a very humid environment may have a shorter MTTF than those operated in a less humid environment, but both MTTF numbers could still be considered “good”.
- Component variability: Not all components are created equal, even within the same category. Differences in material quality, design, or manufacturing processes can all impact MTTF. When comparing results, make sure you’re looking at components of a similar make, model, and manufacturer to get an accurate picture of their MTTF.
- Maintenance and usage patterns: MTTF also varies based on how consistently preventive maintenance is performed and how the asset is used. Excessive workloads or runtime, improper installation, or skipped maintenance tasks can shorten MTTF.
A good MTTF depends on many different variables, but tracking this metric and observing how it changes over time is an important part of successful maintenance management.
Why is MTTF an Important Metric?
MTTF is a critical metric in reliability engineering and maintenance management, offering several key benefits. Firstly, it provides a clear indication of the expected lifespan of non-repairable components, allowing organizations to plan for replacements and manage inventory effectively. By understanding the average amount of time a component is expected to last, businesses can schedule timely replacements, minimizing downtime and maintaining operational efficiency.
Secondly, MTTF is essential for quality assurance and product development. By analyzing the MTTF of various components, engineers can identify areas for improvement and enhance the overall reliability of products. This, in turn, leads to increased customer satisfaction and fewer warranty claims. MTTF also plays a crucial role in cost management. By predicting the lifespan of components, companies can budget for replacements and maintenance activities more accurately, avoiding unexpected expenses.
Furthermore, MTTF is vital for safety-critical applications. In industries such as aerospace, healthcare, and automotive, understanding MTTF ensures that components are replaced before they fail, preventing catastrophic failures and ensuring the safety of users. Overall, MTTF is an indispensable metric that helps organizations improve reliability, manage costs, and ensure operational safety.
MTTF Helps Answer Important Maintenance Questions
Knowing how to calculate MTTF can help your team make strategic operational decisions. Even though it is used for items that can’t be repaired, knowing MTTF for different items your business uses can help maximize uptime and save money.
We can also define MTTF 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 cannot 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 MTTF 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 a run-to-failure approach is more time and cost-effective.
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 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, as well as anticipate supply chain lead time. A CMMS can track an item’s historical MTTF and also leverage it to manage inventory effectively.
MTTF Challenges: How to Overcome Them
Like any other maintenance metric, MTTF presents challenges. For example, maintenance teams can find it challenging to calculate MTTF accurately. Knowing the MTTF formula alone isn’t enough; it’s important to have the right tools, infrastructure, and strategies in place to collect and analyze MTTF data.
Lack of Data for the MTTF Formula
The Mean Time to Failure formula requires a large quantity of data to be accurate; a random sampling of machine failures won’t produce reliable results. For an accurate result when you calculate MTTF, you’ll need a large sample of asset operating times and the number of failures.
Asset Lifecycle Challenges When You Calculate MTTF
MTTF can be difficult to calculate for assets with a longer lifespan. If an asset can run for a long time before breaking down, that makes it challenging to calculate its mean time to failure.
Inconsistent Failure Rates Impact the MTTF Formula
MTTF assumes that assets always fail at a consistent rate. Unfortunately, this isn’t always true. In the real world, conditions are constantly changing; new machines, changing schedules, and environmental factors all impact asset performance and failure rates.
Overcoming Challenges When You Calculate MTTF
MTTF is an important metric, but you should never rely on just one metric or KPI. It’s a best practice to track MTTF along with MTBF (mean time between failures) and MTTR (mean time to repair). That will give you a more complete picture of your asset health.
Using a good CMMS can solve your data collection woes. A CMMS also makes it much easier to track a wide range of maintenance KPIs and metrics.
Learning the Differences: MTTF, MTBF, MTTR, FIT, MTTFd
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 it takes 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 Failure, is used for repairable assets. 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 more slowly 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 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 MTTF 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 to Use MTTF
Tracking MTTF for common items like light bulbs and ball bearings can sound daunting. Correctly calculating this metric requires good recordkeeping, which can translate to lots of paperwork or time spent tracking data in a digital spreadsheet.
However, a CMMS can help you by automatically tracking these metrics. With the help of wirelessly connected sensors, integrated inventory management, and smart software, a comprehensive CMMS like eMaint can generate reports on demand so you have all the MTTF data you need at your fingertips.
When to Use MTTF
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 MTTF 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 lifespan 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
Example of MTTF Calculation in Action
To understand how MTTF can guide real maintenance decisions, let’s look at an example.
A maintenance team wants to calculate the Mean Time to Failure (MTTF) for a batch of 10 identical ball bearings used in a conveyor system. Over time, they record how long each bearing operates before failure:
| Bearing | Hours Before Failure |
| 1 | 3,800 |
| 2 | 4,100 |
| 3 | 3,900 |
| 4 | 4,000 |
| 5 | 4,200 |
| 6 | 3,700 |
| 7 | 4,100 |
| 8 | 4,000 |
| 9 | 3,900 |
| 10 | 4,100 |
To calculate MTTF, add up the total operating hours for all failed bearings, then divide by the number of failures:
MTTF = (40,800 hours) ÷ 10 = 4,080 hours
On average, each bearing operates for about 4,080 hours before it fails. If conveyors run 24/7, that means each ball bearing will last about 5 ½ months. Using this information, the maintenance team can make key operational decisions.
- Inventory Planning: Knowing the average failure rate helps teams predict how many replacements they’ll need over a given time frame. Keeping at least a few on-hand spares for each conveyor line ensures maintenance can replace failed bearings quickly. This also ensures teams don’t over-buy inventory, freeing resources up for other uses.
- Preventive Replacements: If the cost of downtime outweighs the cost of parts, the team might choose to replace bearings before they reach the average failure time. For example, they may decide to replace a bearing at 3,700 hours while the conveyor is already down for maintenance, minimizing downtime. This approach also helps prevent unexpected breakdowns, especially in critical production lines.
- Improve Reliability Over Time: By tracking MTTF through a CMMS, maintenance teams can see if their maintenance actions, such as improved lubrication, better alignment, or vibration monitoring, extend component life. Over time, rising MTTF values show that reliability initiatives are working.
- Monitor Variability: While the MTTF is 4,080 hours, individual bearings failed between 3,700 and 4,200 hours. Analyzing this variability can help identify outliers, such as defective components or improper installation, to improve overall performance.
When consistently captured in a CMMS, MTTF data becomes a decision-making tool that helps balance cost, reliability, and uptime.
How to Improve Your MTTF
Improving MTTF involves several strategies aimed at enhancing the longevity and reliability of non-repairable components. Here are some effective methods:
- Quality Control: Implementing stringent quality control measures during the manufacturing process ensures that components meet high standards. Regular inspections and testing can help identify defects early, reducing the likelihood of premature failures.
- Material Selection: Using high-quality materials that can withstand operational stresses and environmental conditions significantly enhances the durability of components. Material engineering plays a crucial role in extending the lifespan of products.
- Design Improvements: Optimizing the design of components to minimize stress concentrations and improve overall robustness can lead to longer MTTF. This includes considering factors like load distribution, thermal management, and corrosion resistance.
- Environmental Control: Protecting components from harsh environmental conditions, such as extreme temperatures, humidity, and exposure to chemicals, helps in maintaining their functionality over a longer period. This can be achieved through proper housing, coatings, and environmental controls.
- Predictive Maintenance: Using predictive maintenance techniques, such as condition monitoring and data analysis, allows for early detection of potential issues. This proactive approach helps in replacing components before they fail, thereby extending their effective operational life.
- Training and Awareness: Educating employees about best practices in handling, operating, and maintaining equipment ensures that components are used correctly and are less likely to experience premature failures.
Accessing the right data is the first step in improving MTTF, and the best resource for gathering and analyzing it is a CMMS. 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 asset health data, 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 in one location, 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.