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Random failures

Derek Brown

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Hi All,

I am curious about the concept of random/age related failures and wondered...

If 70% – 90% of failure modes are not age-related, how does this actually work in practice?

On my plant we are getting a new item of equipment fitted to replace an old asset, although it is a like-for-like machine, (it is a rotating powder transfer valve - or RAL), does this mean that 70% – 90% of the failure modes on my new equipment are random and i should be utilising Condition Monitoring where i can?
Also, what failure modes are time based only? is it the same failure modes all the time or can these change with asset/conditions/environment/design etc...?

If we try and go with this above statistic, how do we use that on plant, conduct an FMECA to determine the failure modes, score them and then see how these modes are prevented?

When I go to install my new asset I want my maintenance instructions to incorporate these probabilities of failures but how do I actually do this? - does this all link back to an RCM approach? if, so, we do not routinely do RCM/FMECA and we do not have anyone who is trained in RCM, as most of our maintenance procedures are the same since the plant was built 20 years ago, namely mostly time based maintenance. 




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Hi @Derek Brown  when you install a new piece of equipment a large number of failure modes will indeed be random and not age related.

The percentage of random failures depends on the equipment and also the operating conditions for example many corrosion mechanisms are age related (but not all!) which is why for example the submarine data quoted from the SUBMEPP study in 2001 shows a lot more age-related failures (pattern C) versus the original United Airlines (UAL) Study from 1968 (see https://www.roadtoreliability.com/reliability-centered-maintenance-principles/)

And it also depends on your maintenance practices - if you install bearings really well, lubricate them exceptionally well and operate them just perfectly you may indeed experience age related bearing failures. Most organisations don't manage to do that and they never get to age related failure modes on bearings instead they experience random failures because a defect is introduced by e.g. poor lubrication practices.

What you'd want to do is to determine the dominant failure modes for that new piece of equipment, determine the consequence of failure and whether the impact warrants a maintenance action. Then look at the characteristics of the failure mode and whether it is likely to be random or age related. It it's clearly age (or cycle) related than a time based PM can be very cost effective, if it's likely to be random then indeed you want to look at a condition monitoring task.

Bear in mind that a condition monitoring task needs to be practical, cost effective and that the value of knowing that a failure is likely to occur needs to be worth it. If the consequence is really limited a run-to-failure strategy can be perfectly acceptable.  

You don't need to go through a full RCM you could develop a relatively simple FMEA in a workshop with your engineers, maintenance technicians and machine operators. There is likely to be a wealth of knowledge there. And bear in mind that if you are really installing a like-for-like then you can use your historical failure data to determine your dominant failure modes (and then add to that list during the workshop).

Hope that helps?

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