Mean Time To Repair (MTTR)

When it comes to managing your failure metrics for enhanced efficiency, MTTR is one of the essential reliability metrics for the maintenance teams. In essence, the Mean Time to Repair, or Mean Time to Recovery as it is sometimes also called, refers to how quickly an organization needs to resolve incidents. This considers the average time spent on unplanned downtime to troubleshoot and fix equipment failure until it is fully functional again. 

As a rule of thumb in business, the quicker the incident response is and the faster the organization can resume normal operations, the higher the customer satisfaction. As such the mean time to repair MTTR is instrumental to the overall equipment effectiveness. We will explain what Mean Time To Repair is and how to improve it for greater maintenance team’s success. 

Asian male engineers optimizing manufacturing process after calculating MTTR

What is MTTR? 

MTTR typically stands for Mean Time to Repair. However, it can also appear as 

  • Mean Time To Recovery
  • Mean Time To Resolve
  • Mean Time To Resolution
  • Mean Time To Respond

The terms above can be often used interchangeably. However, MTTR measures slightly different aspects of the incident management process depending on the “R” you assign to it. When calculating the incident response using MTTR, it is a good idea to clarify first with the teams in charge which of the “R” will be part of the maintenance contract. This will avoid confusion when measuring and tracking your key performance indicators. By default, this is the repair time.

Time to Repair MTTR measures the time period between the start of the IT incident and the moment of complete recovery. This is a helpful metric that take into account the time to:

  • Notify a team member of the issue
  • Diagnose the root cause of system failure
  • Resolve the issue
  • Allow for equipment cool down
  • Reassemble, calibrate and align the asset
  • Set up, test, and restart production

The MTTR repair time doesn’t account for the lead time teams spent on individual components and parts. 

Understanding the most common incident management metrics

In today’s organizations, system failures can have heavy consequences. From unplanned downtime to small glitches, these can lead to missed service level agreements, project delays, and increased lifecycle costs. 

Therefore, it becomes crucial for operations managers to track and measure system incidents and failures using incident metrics. Incident metrics quantify and monitor how efficiently and quickly the maintenance team can resolve issues and repair processes. 

MTTR is one of those incident metrics along with other incident or reliability metrics, such as MTBF (Mean Time Between Failure), MTTF (Mean Time To Failure), and MTTA (Mean Time To Acknowledge). 

How mean time to repair helps define DevOps incident management

MTTR along with the other reliability metrics are used by the devops team for keeping track of the incident response:

  • How frequently a system failure or an incident occurs
  • The average amount of time the repair process takes before the system is fully operational again

The purpose for the devops incident management team is to manage an IT incident fast and without affecting the overall efficiency. In other words, the maintenance contract should be focused on keeping the response time and recovery time as low as possible. This includes the ability for the organization to invest in protection against potential threats (such as cybersecurity), such as being equipped with the tools and the expertise for neutralizing system attacks rapidly and effectively. 

MTTR results being examined by male manufacturing staff member

How to calculate MTTR

To calculate MTTR of a given asset in the system, you need to distinguish unplanned downtime from scheduled maintenance time for this asset. Scheduled maintenance is typically planned outside of business hours in order to reduce the impact on the production. On the other hand, system failures occur unexpectedly, and they can affect production during business hours. 

The MTTR formula also reflects the asset management strategy of an organization, as it monitors the repair time and the total number of failures over a specific period. It is important to note that failures don’t necessarily mean a system breakdown. It could also refer to a slow system or a system that doesn’t meet its objectives fully, even if it still provides some level of performance. 

MTTR calculation

Typically, MTTR is calculated in hours, but the average time to repair can be measured in any time period, ranging from minutes to days. 

The MTTR formula is:

MTTR= Total Maintenance Time / Number of Repairs 

For example, if maintenance teams spend 20 hours on unplanned maintenance repairs for an asset that has broken down 5 times during a given period, the MTTR is four hours. 

What is a High MTTR?

There is no strict MTTR benchmark as the average time spent on fixing a failed asset will depend on its type, its age, and how critical it is to the system. This will also depend on your maintenance contract service level agreement. 

A good rule of thumb is to keep the average repair time under 5 hours.

Difference Between Common Failure Metrics in System Reliability

The most common performance metrics (also called failure metrics) provide insights into different parts of the function-fail-repair-function cycle. They highlight how prone a system is to failures (aka how reliable it is), and how effective the team is at managing these failures. 

Common Failure Metrics

Some of the most common failure metrics that can also support your MTTR analysis include:

  • MTBF: Mean Time Between Failures measures the time between repairable issues of a system. MTBF can track both reliability and availability in asset management. The higher the MTBF, the more reliable it is. The purpose is to achieve highly repairable systems that don’t encounter frequent breakdowns. 
  • MTTA: Mean Time To Acknowledge tracks the time between the moment the alert system is activated when a failure occurs and the moment repairs start. This focuses on the alert system’s effectiveness and the team’s responsiveness. Ideally, you want to reduce lag time between an alert and the moment the team can work on the failed component to a minimum. 
  • MTTF: Mean Time To Failure measures the average time between non-repairable failures that require a full asset replacement. This calculation can help you understand the expected lifetime of a system and when to schedule maintenance. 

How the Mean Time To Repair Is Different From The Mean Time Between Failures

MTTR and MTBF refer to two different aspects of assessment management operations. MTBF tracks the time between failures while MTTR tracks the repair process duration. Ideally, a healthy system will show a low MTTR combined with a high MTBF.

How the Mean Time To Repair Is Different From The Mean Time To Acknowledge

The MTTA is a complex metric that can help flag significant issues with your alert system. For example, there could be two crucial elements that will increase MTTA, and therefore also affect MTTR:

  • The system needs a long time to identify the failure and send an alert
  • The team needs a long time to respond to the alert 

In the first instance, the integration of intelligent solutions, such as artificial intelligence, can help keep track of the specific health of an asset or a network. 

Artificial intelligence can also be instrumental in reducing alert fatigue, when your team’s response is too slow. This can reduce the number of unnecessary alerts and avoid false alerts. 

Inevitably, improving the MTTA can also improve the MTTR as it ensures the team can start the repair work sooner. 

Signs as alert fatigue are typical of lack of responsiveness to alerts. However, depending on systems, the average amount of time to respond to an alert can vary greatly. Typically, you will be looking at minutes within working hours. But for systems that are not critical or not frequently used, it can be anything from two hours to several days. That’s where an AI alert management solution can help prioritize issue notifications and automate responses whenever possible. 

How the Mean Time To Repair Is Different From The Mean Time To Failure

The Mean Time To Failure calculates how long repairable systems last before they need to be replaced. By tracking MTTF, an organization can also improve its MTTR, as it can implement a better management schedule to avoid an unexpected and irreparable breakdown. 

Asian male engineer calculating Mean Time To Repair of manufacturing machine

How to Use Other Reliability Metrics In MTTR Analysis

As explained, MTTR is only one of many reliability metrics. Therefore, when tracking MTTR, it is essential to keep track of the metrics mentioned above: MTBF, MTTA, and MTTF. The results can create a feedback loop that will deliver improvements to the overall equipment effectiveness and organization efficiency. 

How to Reduce MTTR

It is essential to appreciate that the Mean Time To Recovery for any system relies on multiple factors. By targeting MTBF, MTTA and MTTF, an organization can significantly reduce their MTTR. 

  • A high MTBF means that assets are more reliable, and therefore less prone to failures. Therefore, the total maintenance time is low. 
  • A high MTTF means that the organization has a well-established maintenance strategy. This increases lifetime and reduces lifecycle costs by reducing the number of repairable failures. 
  • A low MTTA means that problems can be rapidly identified and therefore repairs start quickly. 

In conclusion, MTTR, which stands for Mean Time to Repair or Mean Time To Recovery, is a maintenance metric that drives efficiency, along with other meaningful metrics such as MTBA, MTTA, and MTTF. As such, improving one of these metrics is likely to affect the others. 

At OEEsystems, we stand for operational excellence solutions that empower organizations to drive continuous improvement. If you wish to find out more on how to reduce MTTR, do not hesitate to get in touch with our team of experts in house.