Understanding Mean Time to Failure (MTTF)

The effectiveness of your maintenance program depends on regular performance assessment. Conducting performance evaluations and routinely measuring maintenance outcomes can help you identify areas of your maintenance program in need of improvement as well as better predict and plan preventive maintenance (PM) activities. 

Maintenance technicians and reliability engineers use several metrics and Key Performance Indicators (KPIs) to conduct these assessments. One commonly used Key Performance Indicator is Mean Time to Failure (MTTF).

Why is Mean Time to Failure (MTTF) important?

Maintenance programs use Mean Time to Failure (MTTF) to calculate the time a system or component will run before it fails. The metric is typically used to measure run time for non-repairable physical assets—equipment that must be replaced upon failure. Therefore, MTTF is generally used to estimate the expected useful lifespan for a piece of equipment or machinery. This calculation is useful for planning maintenance tasks, lengthening the lifespan of your equipment, and anticipating the eventual need for replacement.

In this discussion, we’ll take a closer look at the formula used to calculate Mean Time to Failure (MTTF), we’ll provide some examples of MTTF in action, and we’ll highlight ways that this Key Performance Indicator can drive improvements in process and productivity

What is Mean Time to Failure (MTTF)? 

Mean Time to Failure (MTTF) is a metric commonly used by maintenance teams, quality control experts, and reliability engineers to determine the average length of time a physical asset will operate before experiencing irreparable failure. 

MTTF can provide a fuller understanding of an asset’s lifespan. This deeper understanding can ultimately contribute directly to preventive maintenance planning, inventory management, and resource allocation around these critical assets. It can also help your maintenance team prepare for replacement and minimize the planned downtime associated with this process. 

MTTF is a valuable metric in several areas of maintenance, including:

• Reliability assessment of critical assets
• Performance benchmarking for equipment and systems
• Preventive maintenance including inspections, upkeep, and proactive parts replacements
• Resource allocation through optimized spare parts inventory
• Cost management, with proactive maintenance significantly reducing repair and replacement costs, and improving financial forecasting
• Continuous improvement, with MTTF revealing patterns in equipment performance that might warrant design improvements or process adjustments
• Compliance with regulations, industry best practices, and safety standards

Calculating Mean Time to Failure (MTTF)

Mean Time to Failure is calculated by dividing the total operational time of a set of identical components by the number of failures within that set over a specific period. 

How maintenance teams calculate MTTF

To calculate MTTF, maintenance teams must systematically track and record operational times and failure events for an asset, or a set of identical assets, throughout the lifecycle. Maintenance teams can calculate MTTF by following the step-by-step approach below.

1. Identify units or components being observed.
2. Track operational time for each unit from the start of use to failure.
3. Document each failure event accurately and precisely.
4. Calculate the total operational time by adding the operational time before failure for each individual unit.
5. Count the total number of failures within the observed set of units.

Factors to track for calculating MTTF

Here are some of the factors you need to keep track of to properly implement the steps listed above.

• Operational time, measured in hours, days, months, etc.
• Number of failures within the set of units
• Operating conditions including environmental factors, load conditions, and usage patterns 
• Maintenance records detailing activities performed before failure
• Component data including manufacturer specifications, warranty information, and expected lifespan

The MTTF formula in action

Now that we understand the factors involved in calculating MTTF, let’s take a closer look at this formula in action. 

The formula for calculating MTTF is:

MTTF = Total Operating Time/Number of Failures

For example:

Let’s say your maintenance team monitors the functionality and lifespan of a specific type of link belt used in 10 identical manufacturing machines. In this scenario, your maintenance team might wish to calculate MTTF for this link belt to plan preventive belt replacement at timed intervals.

Assume, in this hypothetical scenario, 5 belt failures across 10 units over 10,000 hours of total operating time. 

• Where the total operating time is 1000 hours, and the components under review fail 5 times;

10000 hours/5 failures = 2000 hours. 

• Therefore, the Mean Time to Failure for the link belt is 2000 hours.

What is a good MTTF score?  

The definition of a “good” MTTF score is relative and will depend on factors such as the equipment being measured, its operational environment, and the industry in which it is used. This means that an ideal MTTF score, or even a world-class score, will vary widely from one industry to the next. 

Below are a few factors to consider when evaluating the quality of an MTTF score:

• An industry standard MTTF score will depend significantly on the nature of the asset. For instance, industry standards for some automotive components may place the expected MTTF at 5000 hours while the benchmark for a piece of industrial manufacturing equipment may be as many as 50,000 hours. 
• That said, organizations across all sectors generally work to lengthen the useful life of their equipment. Therefore, a good MTTF will be equal to or higher than the basic industry-standard benchmark for a given component or asset. 
• A world-class MTTF will exceed the industry standard MTTF for similar assets operating under similar conditions in a given sector. 
• In all contexts, a comparatively higher MTTF is correlated with longer equipment lifespan, lower costs, and positive maintenance performance; whereas a lower MTTF score may be correlated with more frequent downtime, operational disruptions, and shorter equipment lifespan.

Why is calculating MTTF important? 

Calculating MTTF is important because it provides quantifiable insight into the expected lifespan of your organization’s non-repairable assets. These insights make it possible to make more-informed maintenance, repair, and replacement decisions. 

Below, we take a closer look at some of the benefits associated with calculating MTTF and discuss how these benefits can support process improvements for your maintenance team. 

• Enhanced preventive maintenance scheduling, optimized task planning, and integration with predictive maintenance strategies
• Improved cost management through data-driven budget forecasting, lower emergency repair expenses, and reduced operational disruption
• Optimized spare parts management through improved procurement planning and resource allocation
• Data-driven decision making (i.e. Repair vs. Replace; Upkeep vs. Upgrade, etc.)
• Process refinement through performance tracking, continuous improvement, and improved reliability engineering

Improving MTTF to improve maintenance

There are numerous factors that can impact the MTTF for a given component or piece of equipment including environmental conditions, mode of operation, and its basic expected lifespan. However, the approach that your maintenance team takes to upkeep and preventive maintenance can have a profound impact on MTTF.

Below, we highlight a few ways that your maintenance program can contribute to an improved MTTF, and how this improved MTTF can, in turn, promote overall maintenance excellence.

• Conducting routine inspections helps identify potential issues before they lead to failures and can extend the operational life of equipment.
• Replacing components based on their expected lifespan can prevent unexpected breakdowns 
• Using condition monitoring tools and sensors (i.e. vibration analysis, thermography, oil analysis, etc.) to track the equipment performance can help predict failure and plan intervention in real time.
• Leveraging data analytics and machine learning to analyze historical and real-time data can improve maintenance scheduling. 
• Training operators and maintenance technicians on the appropriate methods for using and managing equipment can prevent misuse, overloading, and malfunction.
• Controlling environmental factors such as temperature, humidity, and dust can slow the impact of normal wear and tear.
• Maintaining an optimal inventory of critical spare parts can facilitate preemptive spare parts replacements, reduce operational downtime, and prevent further damage to equipment.

Maintenance metrics and maintenance excellence

Maintenance metrics provide maintenance teams with several ways to measure the performance of both physical assets and the processes surrounding their care and upkeep. As we have discussed, MTTF is a valuable way to understand your equipment’s useful life expectancy and to make maintenance decisions accordingly. However, physical asset management typically involves tracking a variety of metrics.

Below, we identify a few other reliability and failure metrics commonly used by maintenance teams in conjunction with MTTF: 

• Mean Time Between Failures (MTBF) is the average time between failures of a repairable system and provides insight into its reliability and performance
• Mean Time to Repair (MTTR) measures the average time required to repair and restore a failed system and provides insight into maintenance team efficiency 
• Overall Equipment Effectiveness (OEE) combines data on availability, performance, and quality to provide a holistic view equipment condition and functionality

These metrics can help maintenance teams reach their full potential by providing:

• Baseline performance measurements as a starting point for continuous improvement
• Benchmarking against industry standards as a way of identifying performance gaps 
• Data-driven insights into equipment performance for better-informed decision making, maintenance planning, and resource allocation
• Enhanced reliability and availability through a combination of preventive maintenance planning and predictive maintenance monitoring
• Improved uptime through regular upkeep, preventive parts replacements, and strategically planned downtime for maintenance

To learn more about maintenance metrics and how they can help your maintenance team improve the performance of your critical assets, check out Limble’s Ultimate Guide to Maintenance Metrics.

5 tips for improving MTTF

As noted above, a higher MTTF is generally an indication that your maintenance program is effectively prolonging the life of your equipment and minimizing failure events. Below, we take a look at some of the steps your maintenance program can take to improve MTTF for your critical assets. 

1. Implement a preventive maintenance program that includes regular Inspections, routine upkeep, and preemptive spare parts replacement.
2. Adopt predictive maintenance techniques such as condition monitoring sensors to track real-time equipment performance, predict failures before they occur, and intervene as needed.
3. Leverage advanced analytics for insights into historical and real-time data in order to predict potential failures and implement timely maintenance actions.
4. Train operators on the correct use of equipment to prevent misuse and overloading, which can reduce the lifespan of components.
5. Implement a Computer Maintenance Management System (CMMS) solution that can enhance preventive maintenance through optimized inventory management, improved recordkeeping, and streamlined preventive maintenance scheduling. 

Find out what else the right CMMS can do to help your organization improve MTTF, extend the lifespan of your critical assets, and allow your maintenance team to reach new heights of excellence.