MTBF how to calculate Mean Time Between Failures

What is MTBF and how to calculate the Mean Time Between Failure parameter

The Mean Time Between Failures (MTBF) parameter specifies the average operating time of any repairable device or equipment between multiple failures. Find out why it’s important when dealing with maintenance management.

Mean Time Between Failures (MTBF) is one of the most used performance indicators in the Facility Management sector because it allows you to measure the level of reliability of mechanical and electronic equipment.

If you haven’t heard of MTBF yet and want to learn more about it, this article will provide you with the information you are looking for to understand the meaning, importance and functionality of this parameter, as well as some application examples that will help you understand how to calculate it correctly.

Before moving on, it’s important to underline that the MTBF calculation is based on the collection and analysis of data that have the purpose of accurately describing asset behavior over time. To monitor your organization’s resources, I recommend using an Facility Management software, an essential tool for predicting Mean Time Between Failures, while allowing you to automatically record data relating to individual assets, evaluate equipment performance indices (including MTBF) and schedule targeted interventions that help prolong the life cycle of each component.

What is mean time between failures (MTBF)?

Mean Time Between Failures (MTBF) is an evaluation metric, widely used in the field of Facility Management. It aims at determining how long a mechanical or electronic system is able to operate without interruptions.

A fundamental parameter for all those companies that base their business on the use of more or less sophisticated equipment. The MTBF index allows you to evaluate the reliability and availability of these equipment, defined respectively as:

  • the ability of such systems to perform the required functions under certain operating conditions, for a predetermined period of time;
  • the likelihood that the systems will be fully operational and accessible when necessary.

As it is easy to imagine, the higher the MTBF value, the higher the reliability of the system, as it will be able to operate longer without failures or interruptions.

How to use the MTBF parameter?

Maintenance managers use the MTBF for a better understanding of systems, operational conditions and to understand what to expect from each individual component or machine.

By calculating this parameter, facility managers can formulate preventive maintenance programs that help solve any problems before they occur, minimizing the probability of failure and avoiding long and costly repairs.

MTBF foruma: how to calculate it?

The MTBF parameter provides a reliable assessment of the average expected time between two malfunctions, that is, the period of time that elapses between the occurrence of a fault and the beginning of the next one.

MTBF-Mean-Time-Between-Failures

MTBF-Mean Time Between Failures

 

The calculation of this reliability index is performed by dividing the total operating time of a plant or machinery, by the total number of machine failures (i.e. faults) that occur in the same period.

To calculate the MTBF parameter, the following formula applies:

MTBF =

Total operating time


N°. of faults

The Mean Time Between Failures is usually expressed in hours. Consequently, to correctly quantify this parameter, it is sufficient to divide the total number of hours of system operation by the number of faults that occur in the same time interval.

Examples of how to calculate the MTBF

Consider, for example, a mechanical system designed to operate 12 hours a day. If we assume that the system fails after operating normally for 10 days, the MTBF will be equal to:

MTBF =

N°. of operating hours


N°. of faults

=

12×10


1

= 120 hours

Of course, calculating the MTBF parameter becomes more complex when taking longer time periods into account, during which more failures can occur. Suppose that the same machine, operating for 12 hours a day, undergoes two malfunctionings within three weeks (21 days). The total operating hours would therefore be equal to 252 (12 hours per day for 21 days). The first fault occurs after 80 hours of operating time and requires 10 hours to repair. The second machine shutdown occurs after 70 consecutive hours of work from when the first fault repair and takes 14 hours to repair. In the remaining 78 hours of operation the system is working properly.

MTBF calculation example

MTBF calculation example

Considering the total number of hours the machinery is actually working (i.e. net of the time spent on repairs), and the number of failures occurring during the observation period, the MTBF can be calculated as:

 

MTBF =

N°. of operating hours


N°. of faults

=

80+70+78


2

= 114 hours

It is important to underline that the MTBF formula can only be applied to repairable systems. In the case of plants or equipment that cannot be repaired, it is necessary to use a different evaluation metric called Mean Time To Failure (MTTF).

What’s the difference between MTBF and MTTF?

The main difference between the MTBF and MTTF parameters is that the first one serves to describe the average time that elapses between the failures that occur during the life cycle of an asset. Consequently, it can only be used for repairable components; the second one allows to predict the failure rate of a product that cannot be repaired and that, therefore, once out of use, needs to be replaced.

As with the MTBF, the Mean Time To Failure is also expressed in order of time (usually in hours) but, unlike the first parameter, it takes into account only one fault (the first) and describes the average time expected before the system or machinery undergoes a definitive stop due to this fault. There is no other way to fix it but replace the damaged component.

How to improve the MTBF parameter?

The effects of failures and malfunctions that occur frequently during the useful life of an equipment can be significant and lead to a loss of productivity and an increase in the time and resources to be dedicated to maintenance.

Improving the MTBF means improving the plant’s performance in terms of efficiency and operation cycles, which is why it is important to adopt adequate strategies so that this parameter takes on the highest possible value.

The most effective solutions that allow you to increase the Mean Time Between Failures consist of:

  • improving preventive maintenance processes to transform the approach to maintenance from reactive to proactive, carrying out regular inspections and scheduling small interventions and repairs that prevent the occurrence of more serious failures and minimise the risk of machine downtime;
  • constantly monitoring the operation of assets through the use of specific software that is able to collect reliable data on the actual performance of the equipment, which are necessary to establish in a more precise and detailed manner when and how to intervene;
  • conducting a root cause analysis, known as Root Cause Analysis (RCA), which consists of analyzing a problem to identify its root cause, with the aim of finding a solution that prevents that malfunction from recurring in the future;
  • implementing condition-based maintenance, a particular type of preventive maintenance that bases its effectiveness on monitoring the health conditions of the asset. Consequently, inspections and interventions are not carried out at regular intervals but only after the detection of a decrease in the efficiency of the equipment;
  • using quality spare parts that are able to ensure the best performance of the system over time.

To be able to monitor your asset performance data accurately and reliably, and always get up-to-date information on equipment performance indexes (including MTBF), consider being supported by a Facility Management software, the only tool that allows you to track activities, address problems, plan preventive actions and manage maintenance operations from a single centralized platform in the cloud, accessible anywhere from any device.

 

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