MTBF vs MTTF: What's the Difference in These Failure Metrics?

If your team is looking for ways to plan for and respond to unavoidable system breakdowns, you might be looking for failure metrics like MTBF (Mean Time Between Failures) and MTTF (Mean Time to Failure) to help you calculate and manage downtime.

These metrics offer a straightforward way of tracking the performance and ROI of your internal process, and can offer invaluable insights into the state of your equipment and maintenance measures.

Let’s take a closer look at MTBF and MTTF to learn how to calculate and improve these metrics for smarter incident management.

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What Is Mean Time Between Failures (MTBF)?

Mean Time Between Failures (MTBF) is a reliability metric that’s used to calculate the time it takes for something (machinery, piece of equipment, etc.) to fail and need repair.

MTBF is often used by manufacturers to predict the reliability of their equipment and map out their maintenance schedules with the goal of reducing unexpected downtime.

This metric helps engineers and ops managers understand how dependable their systems are, which in turn allows them to schedule preventative maintenance before expensive failures happen. It can be useful not just to determine how reliable a piece of equipment is, but how good of an investment it is.

How Do You Calculate MTBF?

Here’s a simple formula to calculate MTBF:

MTBF = total uptime / number of failures

Of course, the total uptime refers to the amount of time your equipment or system can run before it fails and doesn’t include downtime for repairs.

If your equipment has a high MTBF output, it’ll have fewer problems in its lifetime, which means less downtime and lower repair costs. If you have a low MTBF output, your equipment likely breaks down more frequently.

How to Improve MTBF

Improving MTBF starts with small, consistent actions rooted in good processes.

To reduce unexpected failures caused by delayed or improper maintenance, make sure to consistently complete each task on time and document it accordingly. Standardizing your procedures, e.g., cleaning, equipment checks, etc., will also ensure consistency and will make it easier for workers to see deviations from the norm before breakdowns happen.

When early warning signs do occur, such as new noises or temperature changes, operators should feel empowered to report these issues as soon as they see them. Early detection is essential to boosting MTBF.

Also, are you collecting failure data? If you’re not tracking failures, you’ll have a harder time identifying trends and focusing your resources where they’re most needed.

A root cause analysis is an essential way of getting to the crux of the failure and to prevent these failures from happening in the future. Involving your operators and technicians in your analyses will provide practical insights that might otherwise be missed.

Other Ways MTBF Can Be Used

A Mean Time Between Failures calculation can be used to set maintenance key performance indicators (KPIs) and make more general operational decisions.

Since MTBF is calculated to estimate when your repairable asset is most likely to fail, you can plan your repair schedule in advance and budget for repairs or replacements accordingly.

MTBF can help you identify which equipment takes priority on the repair schedule. If it has a low MTBF value, its inspections and maintenance can be (or should be) scheduled more frequently. Tracking your MTBF score over time will give operations a measurable way to track progress.

From a business perspective, MTBF data also helps calculate the total cost of ownership and return on investment. In other words, if a new machine or piece of equipment has a high MTBF, it will most likely be a better investment.

An MTBF calculation can help your team identify quality assurance issues by tracking changes in failure rates, which may indicate deeper issues with design, materials, or production processes. Sudden drops may also point to an issue on the plant floor that needs immediate attention.

Some Things to Consider About MTBF

Not all experts agree that MTBF is a useful reliability indicator, and some say that in certain contexts, it can lead to misleading results. Here’s why:

There’s a misconception that MTBF represents how long a piece of equipment will last before it fails. But MTBF is based on statistical averages, not guarantees, and it assumes failures can happen at any time with equal likelihood. It’s more likely that equipment will have already started to fail before it reaches its MTBF. It also leads people to think that MTBF is the minimum time, which sets unrealistic expectations.

MTBF also doesn’t tell you the reason behind these failures, which limits its ability to provide insight. In that case, MTBFs always require root cause analyses. In that case, MTBFs always require root cause analyses. But since equipment failures are always caused by operating factors and not random chance, MTBF doesn’t inherently offer much value in terms of the process of fixing the cause of failure.

Another thing to consider is that averages can be misleading without the full picture.

For example, let’s say you’re testing electric fans.

In Scenario A, you test 20 fans. After six hours, one of them fails.
Total operating time: 20 × 6 = 120 hours
1 failure
MTBF = 120 hours
In Scenario B, you test one fan. It runs for 120 before failing.
Total operating time: 120 hours
1 failure
MTBF = 120 hours

Both scenarios produce the same MTBF, but as you can see, the scenario B fan is much more reliable than the 20 fans in scenario A.

When using MTBF as a failure metric, it should always be looked at with some context.

Now that we’ve covered the average time between failures, let’s take a look at our second failure metric in this post: MTTF.

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What Is Mean Time to Failure (MTTF)?

What is the average lifespan of a non-repairable machine, piece of equipment, or material? Or, in other words, what is the amount of time it takes for a non-repairable attachment, part, or machine to fail? That is essentially what MTTF calculates.

MTTF can help your team plan replacements to minimize downtime, while also improving product design. Not everything in a production line can be repaired (or is worth repairing), so MTTF applies to things like:

Non-rechargeable batteries
Fan units
Bearings and bushings
Light bulbs or indicator lights
Conveyor belts (in some cases)
Filters (air, oil, water, etc.)
Fuses and circuit protection components
Thermal or pressure sensors

How Do You Calculate MTTF?

The formula to calculate MTTF is as follows:

MTTF = total operating time of all units / number of units

So, for example, if your plant floor has 10 cooling fans, you need to take the number of hours they lasted before they failed and add them all up to get your total operating time. You then divide that number by the total number of fans on the plant floor, which in this case, is 10. The resulting number is your MTTF.

How to Improve MTTF

To boost your MTTF, first consider the quality of your components. Parts that cost significantly less to purchase are probably of lower quality and will likely wear out faster, which presents a false economy. Investing in high-quality non-repairables offers a better ROI.

Standardized preventive maintenance plays an important role in improving MTTF. Consider the temperature, vibration, moisture and dust levels. Standardizing certain functions and routine tasks—like checking equipment at regular intervals, lubricating parts, cleaning dust away from components—should be done the same way, every time.

Performance monitoring is also key. Catching issues early can potentially lead to cost savings if you have to replace only small parts instead of larger components.

Some Things to Consider About MTTF

A MTTF calculation assumes that failures are evenly distributed and happen on their own, but it’s not always true. As with MTBF, MTTF doesn’t give you the whole story, or take into account the consequence of the failure or how severe it was.

MTTF vs. MTBF: Differences Between These Two Failure Metrics

What You’re Measuring	MTBF – Mean Time Between Failures	MTTF – Mean Time To Failure
What it Applies to	Repairable assets	Non-repairable components
What it Measures	Failure frequency of repairable assets	How long a component lasts before it fails completely
Examples	Pumps, CNC machines, compressors, production lines	Light fixtures, sensors, bearings, filters
What it’s for	To identify high-risk equipment and improve repair strategies	To help with inventory planning and ensure critical spares are ready
Where it Fits in Your KPIs	Equipment reliability, OEE, planned vs. unplanned downtime	Lifecycle cost planning, procurement, and quality assurance

The Other Metric to Consider Besides MTTF and MTBF: Mean Time to Repair (MTTR)

Not to be confused with Mean Time to Recovery, Mean Time to Respond, or Mean Time to Resolve (all slightly different metrics), Mean Time to Repair (MTTR) is a maintenance metric that shows the average time it takes to diagnose and fix faulty equipment. It essentially measures how efficient an organization is at fixing unplanned equipment breakdowns.

From breakdown to reboot, the following steps are counted when calculating the mean repair time:

The technician is alerted
The problem is diagnosed
Repairs are done
The equipment cools down, if needed
The equipment is recalibrated and reassembled
The equipment is set up properly and tested before being restarted

How to Calculate Mean Time to Repair

To calculate the time to repair your equipment or parts, you divide the number of hours spent on unplanned maintenance by its total number of failures. This calculation assumes that the most qualified technician is performing the maintenance and that the repairs are done in a standardized order.

MTTR = total maintenance time / number of repairs

For example, if your team has spent 120 hours on unscheduled maintenance of a forklift that has broken down three times in the last 12 months, its MTTF will be 10 hours.

What Does the MTTR Calculation Mean for Business?

A short MTTR could mean that your equipment or component is easily fixed and downtime is minimal. A high MTTR score, on the other hand, probably means that your equipment is more disruptive to operations and may cause a more noticeable impact on business.

MTTR offers insights into how unscheduled downtime can affect production, delivery schedules, and overall operational costs. Understanding your MTTR gives you a better picture of how quickly your team responds to failures and how soon operations can return to normal. Aiming for short MTTR points to a well-organized maintenance strategy with a strong culture of responsiveness and problem-solving.

Benefits of Using These Key Failure Metrics in Incident Management

MTBF and MTTF (and MTTR) allow you to leverage your data to understand the status of your equipment, as well as your maintenance strategy and processes over time.

If you’re consistent about using and tracking those key failure metrics, you can expect:

Fewer unscheduled downtimes by identifying equipment and components that are breaking down at a higher frequency
Smarter resource allocation by prioritizing your attention and budget where the risk is highest
More reliable equipment and components by reinforcing preventive maintenance based on data
A better investment by showing which equipment delivers the best ROI

Strengthen Your Incident Response with Failure Metrics

MTTF, MTTR, and MTBF are just some examples of metrics that can help manufacturers better understand the state of their equipment, improve their maintenance practices, and invest in more reliable machinery.