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Reliability is one of the few things that determines the difference between profitability and loss in the industrial sector.
The long-term objective of the maintenance managers and plant operators is the so-called Zero Failures, which implies the continuous operation of equipment with no unexpected failures. Although it is difficult to have zero failures, the highway leading to zero failures is data-driven. Particularly, two important reliability indicators are Mean Time Between Failures (MTBF) and Mean Time to Repair (MTTR).
These measures are not simple figures in a spreadsheet; these are the heartbeat of your maintenance strategy. The industry professionals state that it is expensive to operate equipment until it fails by up to 10 times as compared to running a proactive preventive maintenance program. With the control of MTBF and MTTR, you will be able to switch from fighting fires with the prediction of the same and save much time and money. This guide is going to deconstruct these metrics, the calculation, and how you can use them to propel your organization into a Zero Failure mindset.
Mean Time Between Failures (MTBF) is a reliability metric that measures the average time a piece of equipment operates without interruption between inherent failures. It is a critical indicator of asset health and design quality.
Crucially, MTBF tracks the time passed during normal operation—it excludes the time spent repairing the asset.
Consider the case of an operations manager in a steel plant. They are looking at substituting a huge industrial electric arc furnace with an expensive capital cost. Nevertheless, after considering the data of the MTBF, the manager finds that the machine is not a problem, but certain parts are breaking down regularly. They also do not substitute the whole machine; instead, they substitute only the worn parts.
The Result: The company saves thousands of dollars in capital expenditure and extends the asset's life, all driven by MTBF insights.
Calculating MTBF is straightforward but requires accurate data logging. The formula is:
MTBF = Total Operational Time / Number of Failures
Note: MTBF focuses purely on availability. It does not include the time taken to fix the issue (that’s where MTTR comes in).
Having a high score in the MTBF shows a sound system. This measure is used to determine when a machine is most likely to fail, and hence, manufacturers can schedule preventive maintenance right before it fails and not after the production process has ceased.
When your MTBF is out of industry standards, then it is an indicator that your assets are wearing out or you need to modify your maintenance plan. Here is how to improve it:
While MTBF measures reliability, Mean Time to Repair (MTTR) measures maintainability.
MTTR is the mean time to troubleshoot, repair, and bring up a failed piece of equipment. The clock commences as soon as the failure is realized and ends when the piece of equipment is completely tested and is in production once more.
An example of a thermal heater is an injection molding company that installs a new thermal heater. Surprisingly, the time taken to repair begins to go out of proportion. The manager gets into the data of MTTR and discovers that the technicians have not been exposed to the new model, hence the long delayed diagnostic time. The manager decreases the MTTR by offering specific training that will allow the machine to be put on the line sooner.
In order to determine the MTTR, you have to count the actual duration of time that your group has to spend fixing.
MTTR = Total Maintenance Time / Total Number of Repairs
Insight: Since MTTR is a mean, it is prone to being distorted due to outliers (e.g., waiting weeks to get a part). Nevertheless, it is the most effective measure of detecting inefficiency in your repair process.
The lower the MTTR, the higher the availability. The way to reduce this number is as follows:
Although they may be said to measure opposite halves of the maintenance coin, they are frequently used interchangeably:
Both are essential. You desire high (rare failures) and low (fast fixes) values of MTBF and MTTR, respectively. The combination of these two is what will get the desired metrics of Zero Failure.
Monitoring these measures in a spreadsheet can easily be erroneous and slow. In order to actually be heading in the right direction, towards a Zero Failure environment, you must have real-time information.
Cryotos CMMS is made to automate this intelligence. Being a mobile-first maintenance app, Cryotos enables your company to:
By digitizing your maintenance management, you don't just calculate these metrics—you use them to drive decisions that extend asset life and improve the bottom line.
Achieving "Zero Failure" isn't about luck—it's about intelligence. MTBF and MTTR are the critical metrics that allow you to predict failures and streamline repairs. However, relying on manual spreadsheets often leads to outdated data and costly delays. To truly optimize asset uptime and reduce costs, you need real-time automation.
Ready to Automate Your Reliability Strategy? Cryotos CMMS tracks your maintenance metrics instantly, turning complex data into clear, actionable decisions. Stop guessing and start optimizing today.
