Reliability Metrics 101: Mean Time to Failure (MTTF)

The role of a maintenance and reliability leader is to continuously find methods to optimally use gathered data to track the progress of maintenance activities and to measure the true reliability of their assets.

In earlier articles we shared how Mean Time to Repair (MTTR) and Mean Time Between Failure (MTBF) is used to measure how long it takes to repair and bring an asset back online. However, an important data piece is measuring how long an asset will last before it fails, which is the exact intention of calculating ‘Mean Time to Failure’. Calculating MTTF is a key element in optimizing maintenance and asset management strategies.

Mean Time to Failure (MTTF) is a crucial maintenance metric that measures the average time an asset operates before failure. Effectively, MTTF measures the reliability of non-repairable assets by looking at similar assets over a period of time and measuring how long they perform until failure.

A non-repairable asset is an asset that is generally replaced rather than repaired when it fails as it would be more cost-effective. A few examples of non-repairable assets are lightbulbs, small HP motors, and fan belts.

How to calculate MTTR

Using CMMS software to track maintenance metrics, including MTTF, is crucial for facilitating data-driven decision-making. This approach simplifies the process and supports understanding and monitoring various metrics to improve maintenance programs, shift to proactive strategies, and enhance overall asset uptime and efficiency.

The formula for calculating MTTF as described by the SMRP is as follows:

MTTF = Operating time to failure (in hours) / Number of Assets in Use

Failure = when an asset is no longer able to perform its intended function

Operating time = the timeframe that an asset or component is in operation

It is important to note that this formula assumes a constant failure rate, which may not always be accurate in real-world scenarios.

What is considered a good MTTF?

There is no specific universal benchmark for the MTTF of non-repairable assets. Rather, it is more effective to consider a few factors when deciding whether an MTTF is “good” or not. Among these factors are the expected lifecycle of the asset, the environmental conditions in which they perform, the quality of the installation, and how it compares to like-assets on the site that share a similar use-case.

Accurate MTTF data is crucial for making informed decisions about asset reliability and maintenance planning.

Ways to improve the MTTF for your assets

Conduct a failure analysis

Whenever an unexpected failure occurs, it can prove to be valuable to conduct a Root Cause Failure Analysis (RCFA) or a Failure Mode Effects and Criticality Analysis (FMECA) to help understand why an asset is experiencing a and how to prevent premature failures from happening in the future.

FMECA is a common method used to find problems with the design of a product, the manufacturing process, the materials used, or the installation method.

Consider the quality of the replacement parts used

Consider the context of a personal “asset” like your vehicle. Although there are certain replacement parts that are “good enough,” it can sometimes be counterproductive to use a cheaper or inferior replacement just to cut costs. For example, if you live in an urban setting but replace your city tires with all-terrains, you will lose a significant amount of MPGs which can add up to more fuel costs.

Similarly, using quality replacement parts for your assets, specifically OEM parts, will lead to greater reliable because these parts are manufactured to spec for the asset and use the verifiable materials and processes. In general, a quality replacement part is unlikely to fail due to wear or inadequate manufacturing materials.

Download our “MRO Inventory Best Practices Checklist” to make sure you are ready when it is time to replace parts.

Maintain your assets to keep them in good working order

Preventive Maintenance can often be overlooked due to the common misconception that it only applies to large or complex machinery. However, small motors, pumps, valves, fans, heat exchangers, and other pieces of equipment can all be subject to PM. Scheduled maintenance helps to reduce the risk of unplanned downtime, improves efficiency, and decreases costs. Maintenance professionals play a crucial role in implementing preventive maintenance strategies to ensure asset reliability.

Predictive maintenance is a strategy that uses sensor technology to monitor and predict the health of the asset before it breaks down. These sensors can provide information about the condition of the asset and allow you to take steps to avoid breakdowns. This same predictive technology is used to detect the future failure of a non-repairable asset, which can allow for proper planning for its replacement.

Test new assets on an engineering project

An idea to consider for improving the MTTF of your site is to test a new asset on an engineering project to monitor it and evaluate its true performance and cost-effectiveness.

For example, if your site is considering a new centrifugal pump that is a more expensive replacement, then a new engineering project would be the best testing ground to decide whether it is worth the investment. If the pump is more expensive but lasts longer, then this performance could translate across the entire site.