Mean time between failures (MTBF) and mean time to repair (MTTR) are two very important indicators when it comes to availability of an. The MTTR formula computes the average time required to repair failed equipment and return it to normal operations. Learn how to calculate it with Fiix. 1, MTBF and MTTR Calculator. 2. 3, Month, February, 4, Name of Machine, M_3. 5, Operation availability (min/mo), 24, 6. 7, Frequence, 8. 9, MTBF.

Author: Mogami Julabar
Country: Egypt
Language: English (Spanish)
Genre: Health and Food
Published (Last): 3 May 2015
Pages: 39
PDF File Size: 5.65 Mb
ePub File Size: 8.79 Mb
ISBN: 957-2-80732-338-2
Downloads: 81430
Price: Free* [*Free Regsitration Required]
Uploader: Tujind

Which formula do you use to calculate MTBF? Of course, running hour is better if available.

This leaves out the running time before the first failure and final failure from the caculation. Any advantage in doing this? MTBF is usually applied to a group of similar equipment, for example all the pumps in a refinery. Like Reply 0 Likes. Yes, Cheddar, that’s what I think but somebody said the second formula above should be used because we cannot find the exact start and end dates.

Also it’s time between Mtr, not between the start point and end point. You see those pumps out there. I expect 7 yrs service and will accept 5 and iffen you can’t do it plan on traveling and meeting new mttrr. One approach; training could be another.

Formula for MTBF | AMP Maintenance Forums

Sam, how do calculate your 7 and 5 years? Do you calculate operating time by subtracting the calcu, time before the first failure and running time after the last failure? Originally posted mttt cheddar-caveman: Despite there is some controversy among peers with regard to what is understood by the acronyms MTTF and MTBF, the attached simple example illustrates the way I treat operating data since long with satisfaction from users and no misunderstandings along the way.

From a management perspective, the data accommodates any failure mode. The method can be easily implemented in software and the indicators made available on a timely basis. Of course, many more indicators can be developed at the equipment level to reflect progress in the pursuit of objectives set mtr management. I wasn’t being all that serious before.

Machines are like people, people are like snowflakes – no two alike. You may take an exact model pump and subject it to different environments and industries and come up with different failure rates. Sitting in an office coming up with statistical data doesn’t do anything and I’ve never seen a computer pull a wrench although I have seen it done remotely. Generally the weakest link is the equipments bearing.

It is the first thing to fail usually. Rotors are generally rugged and up to the task as is the shaft and other components. What’s the L10 life of the bearing? Do you realize it? If not roll up your calcuk and get to work: But by getting out there and interacting with people and training on alignment and machinery setup will get you to max MTBF which will be reflected by smiling faces.

It has to go beyond compiling data to get an attaboy. Also your paycheck should increase. Are your machines running longer now than they were two years ago? In 6 years he had written 2 reports totalling 3 pages and no improvements but he had attaboys and pull or draft as the case may be. I recently retained a contract where the head guy wanted to go with a cheaper service vendor.


The techs said, don’t screw with what works, we have mhtr scheduled maintenance and no call-outs and it’s good that way. Of course lightning is hard to predict.

We’ve got so many acronyms now they are hard to keep up with. Seems there’s acronyms for every icon and it’s growing. My soapbox is getting shaky about now!

L10 rating is largely Forget not the effect of contaminants, lubrication, etc, etc. See the ugly red thumbnail in the last segment of http: That is the principal reason why so many bearings which should fail from fatigue keep going well beyond the life estimate: As a rule, the design target is 50, orhours for many machines. It can be higher for electric motors since the bearing size tends to be relative to shaft dimensions, and that last size will be based on force couple and torque issues rather than the very light rotor loads.

It doesn’t mean that you would not cases with a more extensive life: But the previous values of 50K hours standard and k hours by request are good estimates.

What do you mean by Constant time window? Why do you get no. I thought the no. What do you mean by moving constant time window? First we need to understand how do you plant mtte use MTBF in the first place, in my training the formula can be quite confusing and depending on capcul application: I’m looking at MTBF of a machine and a group of similar machines.

From when do you start and finish calculating the loading calucl From the first production date and to today if the machine is still runing ie not decommissioned yet?

Where you “start” your recording is up to you, however, the longer the time period you can use, the more accurate the result will be. Go back to the beginning of your reliable breakdown data. MTBF will also indicate the effectiveness of your maintenance practices and also any steps you might take to improve reliability. kttr

Mean time between failures

For example, in a refinery where I was the Machinery Engineer, we had around pumps of one sort or another. It was an old refinery, aroundand their failure rate was nttr, with an MTBF of around 6 months. I looked back over the failures and identified several caclul failures that kept repeating across the group. The most significant was that most of the pumps had grease lubricated, gear couplings.

Another was that many of the pumps still had packing, leading to expensive shaft replacements etc. Another was poor alignment and there were many premature bearing failures.

Over the next couple of years Calchl replaced all the gear couplings with membranes, upgraded all pumps to mechanical seals and bought a couple of laser alignment kits and trained the guys to use them properly. I also looked at the workshop practices for bearing changes and yes, they were “drifting” the new bearings onto the shafts.

This to me is criminal! I bought a couple of oil baths and some heavy duty gloves. The result of all this hard work, and yes expense, was that after four years the MTBF was at a very healthy 37 months!

At the same time I introduced a vibration monitoring programme along with lube oil analysis and thermography. The most important result from all this was that Operations could plan long runs mtnf we could schedule our maintenance to suite.

Needless to say, there was no war between Operations and Maintenance in this refinery Rolly! Yes, you include the “total population” of your pumps.


Your goal is that ALL pumps fail less often. Our “standby” units were invariably steam-turbine driven, auto cut-in units so that, in the event of a power failure, we could keep clacul and these need to be just as reliable as the main units. To take this discussion to the extreme, if ALL your equipment was only ever on stand-by, your MTBF would be “infinity”, they’d never fail!

Josh, The moving time window is just a convention or a rule to set the time span within which performance indicators PI are to be calculated. Its use is quite common in management performance control at large. It is set arbitrarily though it should be sufficiently long to accommodate several episodes failures in the instance of MTTF or MTBF — the more episodes the higher the accuracy. I should simply have entered 1, hours straight in that cell.

MTTR and MTBF formula excel calculation xls

In this example, only the latest 5 failure matter because the other 2 are already out of the time window, being consequently omitted or discarded. Suppose you are using a time interval of 6 weeks your time window. As time advances, data pertaining to the seventh week back in time are abandoned and new data, this time pertaining to the very last week, are now considered in calculations. When an equipment is under a process of change, it is common practice to give different weights to data — the older the lesser the weight the weights must sum up to 1 — in order to get a picture that anticipates, in a certain way, the changes that are currently on the way.

By doing this, you attribute more importance weight to more recent events and less importance weight to older ones.

There is another method which was baptized “exponential smoothing” that automatically attributes less weight to older data, never “forgetting” any data, regardless of how old they might be. This method doesn’t use the constant time window like the simpler methods I referred above and is less popular among practitioners.

Rui What is the purpose of arbitrarily setting the time span and moving calcup time span forward as time goes by? Is this idea of constant time window the same as constant moving average? Why not just calculate the mtbf since the first failure to today becasue you said the mttf the episode the higher the accuracy?

I need to compare our mtbf values with similar industrial values mtfb also for trending, so I need standard methods of calculating the mtbf. Why do you we need to apply weightage to the data set for equipment under process of change? WHat change do you mean here? Is it modification, operational mode change, operating parameter change, etc? Cheddar Good job for increasing the mtbf for your refinery pumps.

Yes, we could mtte take the straight forward approach that you used i. This composite or overall mtbf allows us to see the improvement from its trending.

For further simplication, did you take the tmtr time period to start from the year of the refinery being built which isrgdless whether any pumps being replaced over the years? Also look like you did not mentioned whether you subtracted any downtime from the operating time period.