MTTR, MTBF, failure rate, maintainability and machine availability

MTTR, MTBF, failure rate maintainability and machine availability

The MTTR, the MTBF, and the failure rates, maintainability and availability rates for a machine are KPIs that may need to be sent to the maintenance manager on a weekly or monthly basis, and are indicators that feature prominently in industrial maintenance training manuals. However, maintenance managers are often faced with a problem, because although their CMMS software may be able to group large amounts of data together, it may not provide the tools for obtaining a dynamic analysis. They are then left to their own devices and find themselves running SQL queries to extract their data or VBA programs to obtain their indicators.

To solve this problem, Mobility Work has incorporated a specially designed tool to help maintenance managers analyse their data in a better way. It also allows any user to view information in a matter of seconds using one of several customisable dashboards.

One of these dashboards covers all of the indicators that tend to be used in maintenance methodology – indicators that are normally quite difficult to generate due to the complex mathematical analyses involved and a lack of tools, time or resources.

MTTR – Mean time to repair

As a general rule, the MTTR is the average time taken by an engineer to clear a fault or carry out a maintenance task. Analysing this indicator reveals how a maintenance service and the engineers’ skills are developing over time. Having a thorough knowledge of a company's machinery and keeping a history of completed maintenance work in a computerized maintenance management system can help improve fault diagnostics and reduce maintenance time. Information previously entered in the CMMS means that engineers can quickly access details of similar repairs carried out by their colleagues, and even jobs they have completed themselves in the past. This is exactly what happens in the Mobility Work maintenance community: in just a few seconds, engineers can gain access to a whole host of users outside their own company who have already experienced the same problem on a similar piece of equipment. So as your maintenance service becomes more and more efficient, your main time to repair will reduce. The analytics module in the Mobility Work CMMS displays the mean time to repair over a given period and compares the trend to the same period in the previous year. This gives maintenance managers an immediate overview of the progress their technical departments are making.

It is also possible to view various dynamic charts to obtain a more general picture of the mean time to repair for a company's machinery:

  • The mean time to repair time to repair by equipment, showing the top 30 pieces of equipment with the highest mean time to repair values
  • The mean time to repair by cost centre, providing a financial breakdown for your company and showing the top 30 cost centres with the highest mean time to repair values
  • The mean time to repair by tag (electrical, mechanical, corrective, preventive, etc.), showing the top 30 tags with the highest mean time to repair values
  • The mean time to repair by maintenance engineer, showing the top 30 engineers with the highest MTTR values

Each chart is dynamic and allows the user to view different curves by clicking on one of the available filters. The search function works in a similar way, allowing the user to filter the MTTR values by searching for a particular term, such as 'motor', in the Mobility Work software.

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Number of activities

An MTTR value is not particularly useful if no data is provided on the amount of maintenance tasks carried out. An mean time to repair of two hours based on only ten maintenance tasks is likely to be a less reliable indicator than an mean time to repair of three hours based on 100 tasks. Knowing the number of jobs carried out is essential for checking the relevance of the mean time to repairprovided.

Mobility Work analytics tool allows you to calculate the amount of maintenance tasks performed over a given period and to view trends. For instance, you can view the number of jobs completed over a chosen period and compare the trend with the same period in a previous year. Logic dictates that as an mean time to repair improves, the amount of maintenance jobs should increase, as the engineers would have more time to carry out other tasks, perhaps by applying the 5S or the Kaizen methodology, or by working on continuous improvement.

MTTR, MTBF, failure rate, maintainability and machine availability

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MTBF – Mean time between failures

The MTBF is the average time over which a piece of equipment operates normally between two failures. It is very often used in manufacturing and can be a reliable productivity indicator. However, the problem with this indicator is that the user requires a certain amount of production data, such as the start times for each operation, the shutdown times and the pause times for the equipment involved, making it difficult to generate the appropriate value.

To address this issue, the Mobility Work computerized maintenance management system bases its calculations on a piece of equipment or a production line operating over one, two or three eight-hour shifts in a day. This way, the startup time is computed automatically based on the chosen option, and the analytics tool can display the MTBF for your machinery. Of course, this will only give you an idea and a general trend for your equipment, but it can be effective in helping you make decisions.

If you use a manufacturing execution system, production software, or sensors that measure your equipment's operating times, these can be connected to the Mobility Work  analytics tool, allowing you to replace the theoretical times with your actual operating periods.

mobile cmms software maintenance management system mttr mtbf

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Availability rate

A machine's availability rate represents the probability of it remaining available for a given period of time. This is calculated by taking account of different time values (actual availability periods, operating times and unavailability periods). As with the MTBF, the availability rate is calculated based on a piece of equipment or a production line operating over one, two or three eight-hour shifts in a day.

The Mobility Work  analytics tool allows you to calculate the availability rate for each of your machines automatically and to identify equipment with availability rates that have declined over a given period.

Equipment life cycle curve

The life cycle curve, or bathtub curve, is perhaps the 'ultimate' indicator in terms of maintenance methodology, helping us decide whether to maintain a particular piece of equipment or invest in a replacement. Unfortunately, this indicator is difficult to implement as its mathematical formula is quite complex and large amounts of data and variables are required. The life cycle curve consists of three phases:

  • An infancy phase, with a large number of failures due to the young age of the machinery and an initial lack of knowledge of the equipment
  • A maturity phase, with a stable number of failures over time
  • An end-of-life phase, with a growing number of failures as the equipment gets older

The Mobility Work CMMS' analytics tool allows you to perform these analyses and to determine the relevant phase (infancy, maturity or end-of-life) for your machinery or equipment.


Maintainability is defined as the probability of performing a given maintenance task within a given period of time. This indicator is also calculated automatically in the Mobility Work CMMS.

And finally ...

The Mobility Work analytics tool also offers the option to generate these indicators (MTTR, MTBF, failure rate, etc.) for a group of companies and to dynamically filter the data by clicking on a particular factory, for example. New indicators can also be added and the dashboards customised accordingly.

You are interested in maintenance management and would like to learn more about this subject in order to increase your productivity and save costs? Let's plan a free online training with our team!

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