In today’s fast-paced manufacturing industry, every minute counts. Delays in identifying and resolving production issues can quickly result in significant losses. That’s why Mean Time to Detect (MTTD) is an essential key performance indicator (KPI) for monitoring the effectiveness of any maintenance strategy.

In this article, we will explore what MTTD is, how to calculate MTTD, and how MTTD compares to other related maintenance metrics like Mean Time to Repair (MTTR), Mean Time to Failure (MTTF), and Mean Time Between Failures (MTBF).

What is Mean Time to Detect (MTTD)?

Mean Time to Detect (MTTD) is a measure of the average time between the moment a problem first occurs and the moment that issue is detected and reported for resolution.

This metric is important to track because the longer it takes your team to detect problems, the longer it will take to fix them. Having a high MTTD can lead to excessive downtime, increased risk of equipment failure, and lost productivity.

How to Calculate Mean Time to Detect (MTTD)

Mean Time to Detect (MTTD) is typically calculated by adding up the total time between every failure and detection over a specified period of time, then dividing that by the total number of failures.

MTTD = (total time between failures and detection) / (total number of failures)

For example, if 10 issues crop up during a given month, and it takes your team a total of 30 hours to detect those issues, the MTTD would be 3 hours per issue (30 hours / 10 issues).

Every organization should attempt to minimize its MTTD. A lower MTTD means that workers – or better yet, automated sensors and software – are quickly identifying problems so that timely corrective maintenance can be performed.

How Do You Track Mean Time to Detect (MTTD)?

MTTD used to be manually tracked and documented using pen-and-paper methods. But most modern organizations today rely on automated systems, such as a computerized maintenance management system (CMMS) like eMaint, to effortlessly, efficiently, and accurately calculate and track MTTD in real-time.

Tracking MTTD can help companies quickly identify potential areas for improvement, helping maintenance teams take proactive steps toward reducing downtime.

How MTTD relates to MTTR, MTTF, and MTBF

MTTD is just one of several metrics used in the manufacturing industry to measure efficiency and productivity. Below is a quick overview of how MTTD compares to other key maintenance metrics:

  • Mean Time to Repair (MTTR): MTTR measures the average time it takes to repair a piece of equipment or resolve a problem. Unlike MTTD, which measures the time it takes to detect an issue, MTTR focuses on the time it takes to fix it. MTTR is important because it helps companies prioritize getting equipment back up and running as quickly as possible.
  • Mean Time to Failure (MTTF): MTTF measures the average time it takes for a piece of equipment or component to fail and become inoperable. This metric is useful for predicting when equipment replacement will be necessary.
  • Mean Time Between Failures (MTBF): MTBF is similar to MTTF, in that it measures the amount of time it takes for a piece of equipment to fail. The difference is that MTBF focuses on assets that may break down but can still be repaired. This metric is helpful in identifying failure trends and patterns, helping companies optimize their maintenance and repair strategy.

While MTTD, MTTR, MTTF, and MTBF are all important metrics for measuring efficiency and productivity in the manufacturing industry, they each focus on a different aspect of the manufacturing process.

By using a combination of these metrics, companies can gain a more comprehensive understanding of their systems and processes, helping them make data-driven decisions that increase both efficiency and productivity.

To learn more, see Maintenance KPIs for Every Role.

How to Improve Mean Time to Detect in the Manufacturing Industry

Improving MTTD requires a proactive approach to identifying and mitigating issues before they become problems. Here are some best practices that your organization can utilize to improve your MTTD.

Implement Predictive Maintenance

Predictive maintenance is a proactive approach to maintenance that relies on data and analytics to identify potential issues before they cause problems. By closely monitoring equipment performance, your maintenance team can predict when asset maintenance will be required, allowing them to take corrective action before any major issues occur.

Implement Continuous Improvement Programs

Continuous improvement programs involve constantly analyzing and improving manufacturing processes with the goal of identifying potential areas for improvement. By continuously monitoring and analyzing data, often with the help of CMMS software, your company can identify and prevent potential issues before they negatively impact your business.

Use Real-time Monitoring

Real-time monitoring allows maintenance teams to detect early warning signs of potential problems, allowing for rapid corrective action. By using automated sensors like those from Fluke Reliability, as well as tracking and analysis software like eMaint, organizations can immediately detect warning signs such as temperature fluctuations, pressure changes, equipment malfunctions, and more.

One of the primary ways manufacturers can improve their MTTD is by investing in advanced monitoring and detection technologies, such as digital sensors and CMMS software. These tools can help your organization detect issues before they become serious problems, quickly alerting operators to potential issues.

By leveraging modern technology, manufacturers can effortlessly reduce MTTD times by having instant access to historical data and analytics, helping maintenance teams identify patterns and trends in equipment performance and take proactive steps to prevent issues from occurring. To learn more, see What is the Best CMMS Software: 4 Key CMMS Features.

Ready to start improving your organization’s MTTD today? Get started with eMaint.