Understanding Mean Time to Failure (MTTF) in Maintenance

Have you ever wished you could see into the future to know exactly when your critical equipment will fail? While no one has a magic crystal ball, there is a metric that can help you predict the lifespan of your assets with remarkable accuracy: Mean Time To Failure (MTTF). Modern predictive models can achieve 92% accuracy when properly trained and optimized. By harnessing the power of MTTF, you can transform your operations, reduce downtime, and take control of your equipment's destiny.

Predicting the lifespan of equipment is key to streamlining operations and reducing downtime. Plus, this knowledge also helps businesses gauge the expected lifespan of their assets and proactively plan to replace them.

Industries that need reliable, high-performing machinery widely use MTTF to help businesses prepare for the failure of non-repairable components, informing maintenance schedules and replacement strategies. By using a data-driven approach based on metrics like MTTF, you can ensure that your operations run smoothly and plan for failures in advance. In this piece, we explore what MTTF means, why it matters, how to measure it, and how it can help you improve your operations.

Key takeaways

• MTTF (Mean Time to Failure) predicts the average lifespan of non-repairable assets, helping maintenance managers plan replacements and manage inventory.
• Calculate MTTF by dividing the total operational hours of a group of identical assets by the total number of assets in that group.
• Use MTTF data to inform purchasing decisions for critical components, schedule proactive maintenance tasks like lubrication to extend asset life, and optimize part stock levels.
• While MTTF applies to non-repairable parts, MTBF (Mean Time Between Failures) is used for repairable assets to measure reliability between breakdowns.

What is Mean Time to Failure (MTTF)?

Mean Time to Failure (MTTF) is a reliability metric that predicts the average operational lifespan of non-repairable assets before they fail and require replacement. Understanding these patterns is crucial since failure rates can vary dramatically based on minor variations in design or operating conditions. This essential maintenance calculation helps facilities estimate how long components like bearings, belts, and sensors will function before breaking down. Understanding MTTF enables maintenance professionals to minimize unplanned downtime, optimize inventory management, and make data-driven decisions about asset replacement timing.

It's easy to confuse Mean Time to Failure (MTTF) with Mean Time Between Failure (MTBF), but they are different. 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.

When MTTF is used

MTTF calculation is primarily used for non-repairable assets—components that are replaced rather than repaired when they fail. This reliability metric helps manufacturers and engineers assess the expected lifespan of products before replacement becomes necessary.

Organizations use MTTF data to plan for replacements, manage inventory levels, and reduce unplanned downtime by anticipating when products will likely fail. For example, if you know a facility lightbulb has an MTTF of 3 months, you can stock replacements in advance for immediate installation. This calculation method is proven effective—when 100 units collectively accumulate 350,000 operational hours before 20 fail, the resulting MTTF of 17,500 hours per unit provides reliable replacement planning data.

Here are common examples of assets where maintenance teams calculate mean time before failure:

• Tires
• Transistors
• 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.

That's where MTTF comes in—calculating it helps you put proactive maintenance plans in place. 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 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 MTTF

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 ensure 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 calculation example

Let's say you want to calculate the MTTF for conveyor belt rollers in your manufacturing facility.

You have 125 rollers that operated 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. That means you'll need to make arrangements for a new roller every 480 hours before the current one fails.

MTTF vs. MTTR vs. MTBF

Remembering these 3 acronyms, their formulas, and when to use each is no easy feat. It's helpful to remember that whenever you come across the phrase "mean time," you're measuring the average time between two occurrences.

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 you buy your assets and parts from quality producers who strictly adhere to quality standards. Durable materials will last a longer amount 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 designed to perform. Additionally, ensure that the conditions such as voltage, pressure, heat, and humidity are right. Always ensure qualified professionals install the assets.
• Start preventive maintenance programs: While you can't repair failed non-repairable assets, preventive activities like cleaning and lubrication extend their operational life and improve MTTF values.
• Use automated PM scheduling: Consistent preventive maintenance execution is critical. MaintainX's mobile-first platform automates PM scheduling, ensuring maintenance tasks are never missed and helping customers achieve an average 32% reduction in unplanned downtime.
• Use meters to collect real-time data: By adding Internet of Things (IoT) sensors to your operations, you can capture real-time data, including temperature, vibrations, and production rates. With reliable data that's constantly updated, tracking failure metrics is simple and can lead to early discovery before problems escalate and cause unplanned downtime.
• Set up a CMMS: A CMMS (Computerized Maintenance Management System) is not just used for scheduling maintenance tasks. Robust reporting allows for quick access to the metrics needed to calculate MTTF. Accurate data can help you identify problem assets that may fail more frequently so you can set up corrective actions before that happens.

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 only serve you for a short period of time before breaking down.

Other types of reliability measurements

In addition to MTTF, facilities use other failure metrics to determine asset reliability, depending on their industry. These metrics enable maintenance professionals to make data-driven maintenance decisions to improve asset uptime and availability:

Mean Time Between Failures (MTBF)

MTBF measures the time between one failure and the next for a repairable asset. MTBF is critical for estimating how long a piece of equipment is available for production before the next unplanned downtime.

While MTBF acknowledges that downtime is inevitable, it doesn't account for planned shutdowns for preventive maintenance activities such as lubrication, servicing, recalibration, and parts replacement. As a result, MTBF can provide insight into 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 9 hours and broke down unexpectedly on 3 different occasions, then its MTBF is:

• MTBF = 9 hours ÷ 3
• MTBF = 3 hours

The water pump works an average of 3 hours before experiencing unplanned downtime.

Mean Time to Repair (MTTR)

MTTR is a failure metric that measures how long it takes to repair an asset and restore it to full functionality. It measures the period from when the initial problem is diagnosed to when normal operations are restored. However, MTTR doesn't account for the time it takes to source replacement parts. MTTR also does not account for planned downtime and maintenance tasks.

MTTR = Total Maintenance Time ÷ Number of Repairs

Let's use the example of the water pump used in MTBF above. The pump broke down 3 times, and the first repair took 30 minutes, while the last 2 repairs went on for 15 minutes each. The MTTR would be:

• MTTR = (30 + 15 +15) ÷ 3
• MTTR = 60 ÷ 3
• MTTR = 20 minutes

That means 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.

While the formulas above are useful, don't feel the need to memorize them. Military standards like MIL-STD-785 emphasize that reliability predictions should be used with great caution and primarily for comparative analysis rather than absolute predictions. Getting a CMMS with native reporting functionality helps eliminate the need to work out complex formulas.

MaintainX, for example, offers built-in reporting features that can automatically track and calculate these key performance metrics, saving you the hassle of number crunching. The software continuously captures real-time data, providing accurate insights into equipment reliability with just a few clicks.

While MaintainX simplifies tracking for MTBF and MTTR, it's essential to understand what these metrics mean and how they compare to Mean Time to Failure (MTTF). Each serves a unique purpose in evaluating equipment performance and maintenance efficiency.

The final word on MTTF calculations

Measuring success and proving efficiency to management can be difficult without the right help. When you pore over spreadsheets and manually track maintenance, you waste time and risk human error. With MaintainX, you can streamline the process and save useful time. Automate your reliability metrics and failure analysis tracking with custom dashboards, and create robust reports that enable data-driven decision-making.

MaintainX doesn't just simplify tracking of important reliability metrics—it helps improve them. Our mobile-first platform bridges the gap between outdated maintenance practices and modern operational excellence, empowering frontline teams to keep the physical world running efficiently.

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