By: Virginia Shram | December 18, 2023
In manufacturing, there are commonly used incident report metrics that refer to specific production line issues. The most common ones are MTBF (Mean Time Between Failures), MTTF (Mean Time To Failure), and MTTR (Mean Time To Repair).
By: Virginia Shram | December 18, 2023
If you work in the manufacturing industry you’ve probably heard of these acronyms – MTTF, MTBF, and MTTR – but you may not know why they are helpful metrics and how to calculate and use them.
Don’t worry, we’ll give you the lowdown of exactly why, when, and how to use these incident report metrics to enhance your product quality and operations workflow.
A basic definition of incident report metrics is that they are indicators of successful and efficient business operations.
For example, a sales company would refer to the number of closed sales per month. By comparing this number to previous months’ numbers, a sales manager would have an idea of whether sales are going well or poorly.
In manufacturing, there are commonly used incident report metrics that refer to specific production line issues. The most common ones are MTBF (Mean Time Between Failures), MTTF (Mean Time To Failure), and MTTR (Mean Time To Repair).
“Mean” refers to the mathematical average. We’ll go into how to calculate these metrics a little further down.
Report metrics are critical tools for a strategic response plan called Incident Management. This involves anything from predicting and preventing future errors to preparing employees for the best way to respond to emergencies and accidents.
Incident report metrics work as excellent KPIs (key performance indicators) for specific company improvement initiatives. For example, a good KPI is having an MTTA (mean time to acknowledge the issue and begin repair) of less than 1 hour throughout all operations.
There are many good reasons for using these metrics as a manufacturer. Ultimately, calculating these numbers will help point to issues in production that could be improved for more reliable operations. Here are some of the most significant benefits:
Mean Time Between Failures is defined as the average time there is between two points of failure in a system like a production line. It is commonly known as a machine’s “average life expectancy”.
One thing to note is that MTBF generally refers to failures as “repairable” because they can be fixed and are expected as a normal consequence of using machinery that degrades over time.
“Uptime” refers to when the machinery is working, either after a repair or after being turned on for the first time.
❌ Note that you should NOT include units which are taken off production cycles for routine scheduled maintenance.
The calculation for Mean Time Between Failures is simple:
A KPI for MTBF would vary based on the company and the type of operations, including machinery, that are available.
Generally, the higher the MTBF number is, the stronger a production system is due to its lengthened ability to work efficiently before failure.
Mean Time To Failure is very similar to the above metric MTBF, with a couple important differences.
While MTBF is used for repairable failures, MTTF is used for non-repairable failures. This is because MTTF assumes that the machines break in a way that is not fixable, and the entire machine must be replaced by a new model.
Calculating MTTF is also relatively simple. If you have trouble conceptualizing this metric, think of it as calculating the average lifespan of a group of people, since death is not “repairable” like a broken part in a machine would be.
⚠ Keep in mind that when you calculate MTTF and MTBF, they may turn out to be the same number. This is normal, and happens when there are multiple machines on the shop floor with failures at the same time.
Mean Time To Repair is closely related to MTBF, except it refers to the average length of time it takes for engineers to fix repairable equipment upon failure.
It is also known by other names such as Mean Time to Response, Repair, Recover, or Resolve.
Mean Time to Repair is yet another metric with a mathematical average:
❌ It should NOT include time spent on repairs that are not directly working on the machine itself (such as ordering a new part or waiting for shipment).
You may want to perform these calculations by hand, but incident metrics are extremely helpful because they are super precise. Solving all these equations manually is not the most efficient nor lean way to go about process improvement.
There’s also slightly more involved math for these metrics that comes into play when manufacturing setups are somewhat complex.
Also, what if someone forgets to note the exact second that a machine fails? Then when you realize there is a missed measurement, the only thing you can do is estimate when the machine failed, which is not exact and could influence your calculations greatly.
The best way to avoid these errors is to use manufacturing software that automatically tracks measurements and collects data. Software solutions like VKS Pro can compile these numbers from data caught directly on the shop floor in real-time and calculate these metrics for helpful insights.
You can also fully integrate your software with your IIoT network so that all operations information is centralized and easily accessible for continuous improvement.
You may hear others referring to variations on these key 3 incident metrics. Here are some of them:
Incident report metrics are one of those routine maintenance tools that should be used regularly in order to keep your manufacturing operations as lean as possible.
Luckily, with digital platform solutions made for manufacturers by manufacturers, it’s a simple process that you can integrate for long-term, valuable insights.