Understanding Mean Time to Failure (MTTF) in Maintenance

Mean Time To Failure (MTTF) is a widely used concept in the field of reliability engineering.

Like its counterpart, Mean Time Between Failure (MTBF), it represents an estimate of the amount of time a system is expected to run before failing.

While MTBF refers to the time between system failures, MTTF refers to the length of time a system can be expected to run without failure. In this article, we’ll take a closer look at MTTF and other commonly used maintenance metrics.

And while you are reading, keep in mind what McKinsey says about digitally enabled reliability:

To capture everything digital can offer in increasing reliability and reducing costs, companies should boost their digital maintenance ambitions.

What Is Mean Time to Failure (MTTF)?

Mean Time to Failure (MTTF) is an essential maintenance metric that estimates how long non-repairable assets can work before they falter. Tracking MTTF minimizes operational disruptions, maximizes asset lifespans, and enables more effective O&M decision-making.

Examples of assets for which maintenance departments calculate MTTF include:

  • Tires
  • Transistors
  • Lightbulbs
  • Forklift wheels
  • Conveyor belt idler balls and rollers
  • Motor or engine fan belts

While such assets are commonly placed on run-to-failure maintenance plans, proactive maintenance, such as preventive maintenance or condition-based maintenance, can help extend their lifespans even more. There are many situations when calculating MTTF can help improve an organization’s asset management strategy, such as:

  • Equipment and Parts Purchasing: Prioritizing items with high MTTF ensures that organizations purchase high-quality, durable materials with extended useful lives.
  • Maintenance Scheduling: MTTF can help inform preventive maintenance schedules for non-repairable assets to prolong their life cycles or that of their components. For example, you can’t repair the bearings of a manufacturing machine, but lubricating them can extend their lifespan.
  • Inventory Management: MTTF can help establish a “just-in-time” inventory management program. Once you establish your asset’s MTTF, you can arrange for a replacement just before the asset fails—no sooner and no later.

MTTF helps maintenance teams develop effective maintenance strategies, reduce dependence on reactive maintenance, and decrease unplanned downtimes.

How to Calculate Mean Time to Failure

To calculate MTTF, divide the total time of operation by the total number of items you are tracking:

MTTF = Total Hours of Operation ÷ Total Number of Assets in Use

Only calculate MTTF for identical assets and parts: their manufacturer, size, and even usage should match.

For example, let’s say you’re calculating the MTTF of lightbulbs in your inventory.

You would want to make sure that the lightbulbs are the same wattage, built by the same manufacturer, and used in the same way to ensure a more accurate MTTF value.

MTTF Example

You want to calculate the MTTF for conveyor belt rollers in your manufacturing facility.

You have 125 rollers that have been used for a total of 60,000 operational hours in the past year. The MTTF is:

MTTF = Total Hours of Operation ÷ Total Number of Assets in Use

MTTF = 60,000 hours ÷ 125 assets

MTTF = 480 hours

The average lifespan of a conveyor belt roller at your production facility is 480 hours. You will need to make arrangements for a new roller every 480 hours before the current one fails.

How to Improve MTTF

So, how can you improve MTTF to get more out of your assets before they fail? Here are a few tips to get started:

  • Purchase quality materials and parts: Always ensure that you buy your assets and parts from quality producers. Purchase materials produced in strict adherence to quality standards. You’ll have durable materials that will serve you for a longer period of time.
  • Use assets only for intended functions: Purchasing quality materials isn’t enough. You also should use the assets and parts only for the functions they are intended to perform. Additionally, ensure that the conditions such as voltage, pressure, heat, and humidity are right. Always have the assets installed by qualified professionals.
  • Implement an effective preventive maintenance program: There’s little that maintenance scheduling can do for assets that are running to failure. However, preventive maintenance activities such as cleaning and lubrication can help to extend their lifespan. Developing and implementing an effective PM program can help to improve your MTTF.

To a certain extent, proper inventory control also can help improve MTTF. When you overstock your inventory and materials stay for too long in the warehouse, they will likely get damaged, rusty, or expire. Faulty equipment and parts will serve you for a short period of time before breaking down.

Other Types of Reliability Measurements

In addition to MTTF, facilities use two other failure metrics to determine asset reliability. They enable maintenance professionals to make data-driven maintenance decisions to improve asset uptime and availability:

Mean Time Between Failures (MTBF)

MTBF is the amount of time an asset can operate before experiencing failure. It measures the time between one failure and the next. MTBF is critical to estimating how long production can use an asset before the next unplanned downtime. It acknowledges the fact that failure is inevitable.

The metric is only used for repairable assets. However, it doesn’t take into account planned shutdowns for preventive maintenance activities such as lubrication, servicing, recalibration, and parts replacement. As a result, MTBF measures both asset availability and reliability. The higher the MTBF, the more available and reliable the asset.

MTBF = Total Uptime ÷ Number of Failures

For example, if a water pump operated for nine hours and broke down unexpectedly on three different occasions, then its MTBF is:

MTBF = 9 hours ÷ 3

MTBF = 3 hours

The water pump works an average of three hours before experiencing unplanned downtime. Keep in mind that MTBF doesn’t factor in planned maintenance. So any planned shutdowns during that period aren’t included in the calculation.

Failure in Time (FIT)

Another way to report MTBF is Failure in Time (FIT). FIT helps estimate an asset’s operational lifetime. It reports the number of expected failures for every one billion hours of asset operation.

A Confidence Limit is then assigned to the asset. A Confidence Limit of 95 percent usually means that failure won’t occur often. Component and semiconductor manufacturers are the primary organizations that use FIT.

Mean Time to Repair (MTTR)

MTTR is a failure metric used to measure how long it takes to repair an asset and restore it to full functionality. It takes into account the period from when the initial problem is diagnosed to when normal operations are restored.

MTTR = Total Maintenance Time ÷ Number of Repairs

Let’s use the example of the water pump used in MTBF above. The pump broke down three times, and the first repair lasted 30 minutes, while the last two went on for 15 minutes each. The MTTR would be:

MTTR = (30 + 15 +15) ÷ 3

MTTR = 60 ÷ 3

MTTR = 20 minutes

It takes an average of 20 minutes to repair the water pump each time it breaks down.

When calculating MTTR, it’s important to note the following:

  • MTTR only gives you the average repair time; some breakdowns can be severe and, therefore, take longer to repair.
  • Repairs should be handled only by trained and experienced professionals; otherwise, you might not get reliable MTTR values.
  • You may need to eliminate outliers that prolong the repair process and skew the results when you have a small sample size.

MTTR measures the average time it will take to identify the cause of asset failure and fix it. It gives an idea of how quickly the maintenance team can respond to unplanned downtimes and restore asset functionality. When calculating MTTR, factor in the period from when the asset failed to when it resumed normal operations. This includes:

  • Maintenance technicians being alerted about the downtime
  • Performing diagnosis on the asset and identifying the issue
  • Performing maintenance on the asset
  • Reassembling, realigning, and validating the asset after maintenance
  • Resetting, testing, and restarting the asset for production

It’s worth emphasizing that MTTR doesn’t take into account the amount of time it takes to source replacement parts. It’s also not used for planned downtimes and maintenance tasks.

Using modern computerized maintenance management system (CMMS) solutions can help automate MTTR calculation for critical assets. A CMMS can automatically log the data when maintenance technicians open and close work orders. With that said, it’s not uncommon for folks to confuse MTTF and MTTR:

What Is the Difference between MTTF and MTTR?

It’s helpful to remember that whenever you come across the phrase “mean time to . . .” you’re measuring the average between two occurrences.

Just like MTTF, Mean Time to Repair (MTTR) is another important failure metric that can help you improve your asset maintenance management.

MTTR is a good baseline for identifying ways to improve maintenance efficiency and reduce unplanned downtimes. It also helps identify what makes maintenance take longer than normal. MTTR gives useful insights into how to purchase replacement parts and schedule maintenance activities.

The major difference between MTTF and MTTR is that MTTF is only used for non-repairable assets, while MTTR is used primarily for repairable assets. MTTF is the amount of time it takes before an asset fails and needs to be replaced. MTTR, on the other hand, is the average time it takes to repair an asset after a downtime.

Track Maintenance Metrics with MaintainX

As an asset maintenance manager, it’s your responsibility to ensure maximum asset uptime and availability.

Understanding MTTF and the other failure rate metrics can help identify ways to improve and optimize your maintenance programs. These metrics are key to shifting from reactive maintenance to a proactive strategy. The good news?

Mobile software like MaintainX, as shown above, makes it easier than ever to track essential maintenance metrics, oversee maintenance scheduling, and manage parts/inventory! Click the banner below to download the world’s top-rated CMMS for free.


What Does a High MTTF Value Indicate?

A high MTTF suggests that a device or system is expected to operate reliably for an extended period before the first failure, which can be desirable in many applications.

Is MTTF a Guarantee That a Product Will Last That Long?

No, MTTF is a statistical estimate based on historical data and assumptions. Individual units may fail before or after the MTTF value.

How Can I Improve the Reliability of My System Based on MTTF Data?

Analyze failure patterns, address common failure modes, and implement maintenance and design changes to improve reliability. A CMMS integration can also significantly improve the reliability of these systems.


How long does it take to implement MaintainX?

For the average customer, it takes three weeks to implement one site. For customers on our Premium & Enterprise plans, our team ensures a smooth transition to MaintainX within your organization. Partner with a dedicated implementation specialist through our structured three-week onboarding process. Learn more about our Implementation services here.

Is MaintainX secure?

MaintainX is compliant with security standards, including SOC 2, ISO 27001 & GDPR. It also supports Single Sign-On (SSO), multi-factor authentication (MFA) and custom permissions and roles. For more information, visit our Trust Center page.

Does MaintainX support multiple sites?

Yes, MaintainX Enterprise allows you to manage multiple plants or facilities within the same platform. You can also create customized reporting dashboards to track KPIs across multiple sites on the same screen.

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Caroline Eisner

Caroline Eisner is a writer and editor with experience across the profit and nonprofit sectors, government, education, and financial organizations. She has held leadership positions in K16 institutions and has led large-scale digital projects, interactive websites, and a business writing consultancy.

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