Research & Best Practices

What is Mean Time Between Failure (MTBF)?


What is mean time between failure? This metric — commonly referred to as MTBF — is a frequently used reliability indicator, measuring the average amount of time that a piece of equipment is operational (uptime) before it requires intervention in the form of repair or replacement.

As an averaging metric, measured in aggregate, MTBF is most useful in measuring overall performance and maintenance effectiveness and efficiency. MTBF should not, for example, be used as a predictor of when a piece of equipment might fail, or when it should be examined.

In other words, a MTBF of 100 hours does not mean that that interval is exactly when a particular part is expected to fail or require intervention. That metric should instead be used to compare against benchmarks and previous performance to determine whether production and maintenance are operating efficiently, effectively and as intended.

In this article, we will explore how to calculate mean time between failure and how to use this key performance indicator (KPI) once you have attained a usable calculation. Read on to learn more.

Calculating mean time between failure (MTBF)

While mean time between failure can be used in many ways, it always follows the same formula. The mean time between failure formula for a piece of equipment or a component over a set time period is as follows:

Total operational time / number of failures

In other words, MTBF for a piece of equipment is arrived at by dividing the total amount of uptime over a given time period by the number of breakdowns of that piece of equipment over the same time.

For example, let us assume that over a two-week time period, a piece of equipment is operational for 100 hours. Over that same time, two failures occur. Apply the formula:

  • 100 hours of uptime / 2 failures

We arrive at an MTBF of 50 hours.

Now, assume that the manufacturer had been keeping records of failures and decided to look at MTBF over the past 6 months. The manufacturer uses the same formula, plugging in data from the last 6 months, over which the equipment had experienced 6 failures during 1200 operational hours.

  • 1200 hours of uptime / 6 failures

The calculation gives an MTBF of 200 hours.

Comparing these two metrics against one another, the manufacturer can be reasonably confident, given the statistically significant divergence between the two, that the equipment may require maintenance, repair or replacement and can carry out further diagnostics and investigation to remedy the situation.

In this scenario, MTBF delivers value by providing direction on maintenance efforts and may also reduce or prevent unnecessary and unplanned downtime, which can significantly negatively impact the efficiency and productivity of the facility.

How to improve MTBF

As a reliability metric, MTBF is a useful indicator of potential inefficiencies in maintenance operations and production optimization. The MTBF meaning in maintenance is particularly useful for targeting resource allocation to equipment and areas that can most benefit from intervention.

Ways of improving MTBF include:

  • Preventive maintenance programs: A scheduled PM program remains an effective way to extend equipment life and to extend time between failures. Many equipment failures occur due to simple neglect and lack of attention. For example, equipment that is not regularly wiped down and cleared of debris at the end of each shift is far more likely to experience contamination and increased wear and tear due to the presence of unwanted material. An efficient, tested preventive maintenance program can extend MTBF and thus help gain more value out of equipment.
  • Machine health monitoring: Machine health monitoring is a big-picture assessment of equipment productivity and performance. By tracking performance data, including uptime, output, suboptimal operation and maintenance events, machine health monitoring can assess whether equipment is being properly operated and maintained. Poor MTBF metrics will naturally have a negative effect on machine health monitoring metrics, and so the tactics used to improve machine health as a result of this approach can help to extend MTBF.
  • Industrial sensors: Industrial sensors play a role in nearly every advanced method of improving facility productivity and are a key component of measurement for machine health monitoring as well as KPI monitoring like MTBF. These sensors — whether integrated as an onboard part of equipment, or currently, more commonly, installed as aftermarket components — deliver real-time, actionable data that can be recorded, analyzed, displayed on dashboards and used to calculate metrics like MTBF.

MTBF is one tool in an ecosystem of valuable, useful KPIs. Another such metric is MTTR, or mean time to repair, which can often be confused with MTBF. MTTR measures the time from which a failure state is detected, or a maintenance need is identified, until the scenario has been remedied and the equipment is again operational.

This metric applies only to unplanned maintenance, and while it provides highly useful insight into the efficacy of maintenance operations once they are required, it differs from MTBF — which can be used to, ideally, increase the amount of time that lapses before maintenance is needed.

At ATS, we are experts in maintenance and reliability and understand the importance of reducing MTBF as a core KPI.  Contact us to learn more.

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