There are three common failure metrics critical to effective maintenance management these metrics are MTBF MTTR- a mean time to repair (MTTR), mean time between failures (MTBF), and mean time to failure (MTTF).
It is the average amount of time required to repair and restore a system to full functionality by adding the total time spent on equipment repairs in a given time frame and dividing that by the number of total repairs in the same time frame. you’re able to find your meantime to repair. MTTR is an important tool for any organization because it tells you how efficiently your maintenance team responds to issues with your assets.
it is the average time between two failures of a system it can be calculated by taking the total operational time of an asset and dividing it by the number of failures that occurred within that period. MTBF can provide insights into the thoroughness and effectiveness of unplanned repairs.
so on the the other hand is the average time until the first failure of a system. it can be calculated by taking the total operational time and dividing it. by the number of systems that fail within that period. MTTF is a valuable way to assess the effectiveness of equipment setup and operator training accurate data is important for all three metrics
you need to collect maintenance history including the expected operating hours per week. asset downtime and how long it takes to get assets up and running again if they fail. A cmms like Limble can streamline data collection for metrics like these when you use Limble’s custom dashboards you’ll be able to create your KPIs and see your critical maintenance metrics like MTTR, MTBF, MTTF, and more in real-time.
You can also view a live custom dashboard that your team and the rest of the company can see eliminate guesswork make informed decisions and keep operational disruptions down to a minimum.
MTBF is the average time between system breakdowns and how you calculate it is the number of operation hours divided by the number of failures. and the result will be in hours. so, for example, if a machine has been operating for a thousand hours in a year, then the asset of the machine broke down eight times. therefore mean time between failure for the piece of equipment is 125 hours. so why do we care why do we want to know this why do we want to know the mean time between failures of a piece of equipment well the reason?
EXAMPLE OF MTBF:-
we do this for example because of maintenance and to ensure that we have an effective maintenance program place you need to know the likelihood of when your equipment is going to break down. so you don’t want to be chasing issues because what happens then well your lines go down. you have problems where you can’t meet your customer orders. because equipment has broken down. without any unplanned events have occurred. you didn’t think it had stopped during a shift and it did the piece of equipment and therefore you have to bring maintenance people in to have a look at it. but the whole idea is that you would have a preventative maintenance program in place in a company so instead of waiting for the equipment to break down.
maintaining that equipment:-
you would be maintaining that equipment before anything goes wrong and calculating the mean time between failure for pieces of Machinery helps you have a very effective maintenance program. and it’s a mean time between failure is very important metric in a prevention and preventative maintenance program and it’s used to help plan scheduled maintenance so in other words because you know when equipment is likely to break down you build. it into your maintenance schedule. and it also uh ensures that you have a very tight vintage maintenance schedule and that you know you are maximizing your technicians.
so they’re working on the right equipment at the right time it’s also beneficial because it ensures that you keep your stocks off spare parts low so you don’t want to be holding lots and lots of spare parts in your warehouse for when you might do maintenance you want to keep those stocks low because carrying inventory costs money so by having knowing your mean time between failure for your different pieces of equipment.