Menu
What Is Mean Time Between Failures (MTBF)? Definition, Calculation, Benefits

What Is Mean Time Between Failures (MTBF)? Definition, Calculation, Benefits

There are many reasons why industrial and manufacturing companies measure mean time between failures (MTBF). These reasons include determining how frequently a piece of machinery breaks down so that the right maintenance and repairs can be carried out before the asset causes undesirable downtime or halts production processes.

In addition to this, measuring and monitoring mean time between failure results in greater overall system reliability due to improved asset performance. As such, measuring this metric is crucial. However, it requires an understanding of mean time between failure’s meaning, knowing how to calculate MTBF, its role in manufacturing as well as its advantages.

These are the topics that this article explores. So, keep reading to discover MTBF’s meaning and why it is a crucial metric for your organisation.

 

What Is Mean Time Between Failures (MTBF)? Definition, Calculation, Benefits

What Is Mean Time Between Failures (MTBF)?

If your first question in our exploration is “What does MTBF stand for?” the answer is “mean time between failure.” But what is mean time between failure?

To answer the question “What is MTBF?” we outline a brief definition of mean time between failure as follows: it is a quantitative and maintenance metric that measures the average operating time (expressed in hours) between the failure rate of a given asset or system within a manufacturing or industrial environment. It is used to measure the performance, safety and equipment design of complex or simple machines.

In this MTBF definition, it is also important to emphasise that the MTBF formula focuses on unplanned maintenance only. It, therefore, does not take into account scheduled maintenance or planned maintenance, which may include aspects such as inspections, recalibrations or preventive part replacements.

Mean Time Between Failure Calculation

calculator

An MTBF calculation requires using a specific mean time between failures (MTBF) formula. While the MTBF equation is quite straightforward, it should be noted that there is no industry average that serves as a benchmark for what a good MTBF score is.

This is because every industrial or manufacturing organisation deals with different types of equipment with differing warranties and lifespans. This means that each piece of equipment’s longevity will depend on numerous factors that cannot be collated into an average that the industry can use.

However, as a rule of thumb, the higher the MTBF value is in terms of hours, the better the performance of the piece of machinery in question due to longer operation time. Below, we outline the mean time between failure formula to help you calculate MTBF accurately.

Calculating MTBF:

MTBF = Total time in terms of the number of operational hours ÷ Total number of breakdowns or failures

Here is an MTBF formula with an example:

In terms of the total number of operational hours, say that there are eight productive hours per day for the machine in question. There are five days in a working week when this machine is productive. In addition, there are 52 weeks in a given year. This means that 8 x 5 = 40 and 40 x 52 = 2,080.

As such, there are a total of 2,080 hours in a year when the machine should ideally be working. However, if there are, say, five failures during the year, we would divide 2,080 by 5 to get 416 hours. This is the MTBF. It essentially means that the machine will, on average, operate for 416 hours before its next failure or breakdown. This can help reliability engineers carry out a stronger root cause analysis of productivity and improve total uptime as the maintainability of assets becomes more predictable.

MTBF in Manufacturing

The importance of measuring mean time between failures in the manufacturing industry cannot be overstated. That is because it has a strong relationship with maintenance management through maintenance and reliability. However, it is also worth pointing out that MTBF and MTTR (mean time to repair) have a strong correlation as well.

That is why only calculating MTBF is not a sound practice. This is because measuring the average time it takes to repair a piece of equipment or machinery plays a huge role in the reliability of a system and how much downtime the organisation experiences as well as how long production processes are halted.

How to Improve MTBF in Manufacturing

Every maintenance manager and maintenance team seeks to reduce downtime and increase the MTBF metric at their organisation. However, this is not always an easy task to accomplish due to the fact that there may be many assets in operation, each with its own lifespan and specific preventive maintenance requirements.

Consequently, when you focus on increasing MTBF within your organisation, you will benefit from increased uptime. This requires keeping track of the MTBF metric for each piece of equipment, particularly those that require continuous operation. For this purpose, it is necessary to efficiently schedule your maintenance activities. However, there are other factors to consider as well. These include:

  • Design improvements: As a starting point, you may wish to consider making design improvements to the layout of your production facility. You may also wish to focus on using higher-quality materials, incorporating measuring redundancies or even improving the design of critical components.
  • Preventive maintenance: Also referred to as preventative maintenance, preventive maintenance is a proactive approach to regularly maintaining and inspecting assets before they break down in order to identify issues that can lead to equipment failure. Preventive maintenance tasks may include aspects such as lubrication, cleaning of parts or affected areas or even replacing worn or damaged parts.
  • Training and education: Another method for improving MTBF at manufacturing facilities is investing the necessary time and resources into training and educating your maintenance teams to identify potential issues and carry out maintenance tasks correctly. Aspects you may wish to consider include following accurate operation procedures, using the right troubleshooting techniques and carrying out maintenance tasks efficiently and effectively.
  • Data analysis and monitoring: With accurate and real-time data at your disposal, you can make better decisions regarding when to schedule maintenance activities and how to optimise your machines’ lifespans. Some examples of data you can use include sensors, logs and other sources, which can help you identify potential problems and address these before they result in a failure.

Want to know what's the difference between downtime and idle time? Our in-depth article about idle time covers it all.

Benefits of Improving MTBF

There are numerous benefits of improving your organisation’s MTBF metric. Among these benefits are: 

  • Improved reliability: When you are able to better predict MTBF, you can take proactive steps to ensure that machine failures are far and few in between. This means that through preventive maintenance efforts, you can reduce breakdowns and improve equipment uptime and reliability.
  • Better safety: Machines that operate at their optimal capacity and are regularly maintained lead to fewer breakdowns and fewer safety hazards, both in terms of your maintenance team’s safety and the people on your production floor.
  • Cost savings: The fewer machine breakdowns you encounter, the more cost savings you will enjoy. This is because equipment failures can often halt production processes due to emergency repairs that need to be carried out. This takes teams away from other priority tasks and is time-consuming to fix. When you don’t have such challenges, your cost savings will be greater.
  • Longer equipment lifespan: When a machine operates reliably and with fewer breakdowns, it means it can operate for longer periods of time according to the manufacturer’s guidelines. This means fewer investments in new equipment and an extended lifespan of your machinery.
  • Enhanced customer satisfaction and brand reputation: Reliable and punctual production that is easy to predict means fewer quality assurance issues and defects. It also means timely delivery of products to end customers. When your organisation is known for these qualities, you have a greater chance of boosting customer satisfaction and loyalty as well as enhancing your brand reputation in the industry as a reliable product manufacturer.

Let Fabrico CMMS Help With Preventive Maintenance

fabrico website

If you are on the lookout for specialist MTBF tools that help you accurately measure and predict mean time between failures and other related metrics, then Fabrico’s computerised maintenance management system (CMMS) is an excellent choice.

This tool is perfect for preventive maintenance tasks and what is more, it yields insightful data analytics and reports that measure key metrics and performance indicators to ensure your operations are as efficient and streamlined as possible.

To explore this maintenance management tool in more detail and enhance your efforts through powerful preventive maintenance software, don’t hesitate to reach out to us.

Conclusion

The significance of measuring MTBF in maintenance cannot be underestimated.

This crucial metric shows you the reliability of your machines and enables you to make calculated decisions on how soon they are expected to break down. As a result, allowing you to take preventive measures to address potential equipment failures.

If you want to optimise your maintenance strategies, we encourage you to learn more about Fabrico’s CMMS as a potent tool that helps you streamline operations, measure the right metrics and make crucial data-driven decisions that help your organisation thrive.

Latest from our blog

Still Wondering?
Check for Yourself!
Still Wondering?

Schedule a 1-to-1 meeting with our experts or directly enroll in our Free Plan.
No Credit Card required!

By clicking the Accept button, you are giving your consent to the use of cookies when accessing this website and utilizing our services. To learn more about how cookies are used and managed, please refer to our Privacy Policy