In this post we get a little heavy as I try to explain that while age is relevant, it is not the sole (or even, in the majority of cases, the main) determinant of an assets life.

For those of you expecting something a little more lifestyle oriented based on the title I apologise in advance as this is not really about your personal life choices and why a bit more exercise and a little less alcohol will help you stay young - but keep reading anyway as you never know you may learn something (and they say that continued learning helps stave off the effects of aging on the brain :)).

The problem that I am seeking to address is that, within many organisations, there is scant understanding of how assets truly perform and in many cases this results in increased business risk or poor investment decisions. Put simply I would like everyone to be aware that there are a number of failure patterns that apply to assets and they are not all associated with age.

Now, before we start, I just want to be clear that I am not intending this to be the last word on this topic (there are forums on LinkedIn for that sort of thing and plenty of practitioners, including myself, that will wax lyrical and in detail on the merits of a proper approach to maintaining your assets if you want this - and not all of us have beards and/or are socially challenged). It is also prudent to point out that I do not consider the shortening of operational life driven by obsolescence in this blog (which is where an asset is no longer wanted or parts are no longer available even though it is in good working order). If you want an example of this then consider my partners’ iPhone 3S, which while still in perfect working order, can no longer receive software updates making it technically obsolescent (‘nuff said).

So with the preamble over, what do you need to know about the aforementioned failure patterns…

Well, there are six of them and only three are associated with age (and combined these three only equate to approximately 11% of total assets). The other three are not related to age (ignoring obsolescence) and are considered random. Have a look at the diagram below to see these represented graphically. Some gentlemen called Nowlan and Heap discovered this while examining the causes of failure in jet aircraft in the 1960’s and 70’s and their work produced RCM (Reliability-Centred Maintenance) which was then developed into RCM2 by the late John Mowbray .  

Diagram showing different failure patterns (sourced from www.reliabilityweb.com)

Codswallop I hear you cry (or something similar) everything has a life! Well my good man/lady let me explain the concept of asset “life” by applying this to us human beans. Now I think one thing we can all agree on is that, notwithstanding massive advances in medical science, we are all going to depart this mortal coil at some point ☹. We just don’t know when and more importantly we are not all going to do so at the same age (neither will we have the same level of functional capability at the same age either).

Now if we apply this process into the physical asset space and consider say a number of identical pump bearings then we may expect some to fail within the first few months of operation, some within the first couple of years, a few between 3-5 years and a handful after 10 years of operation. So what “life” do we attribute to our pump then – can we take the average? Let’s say the average is 3.6 years if we take this as the life of the asset then how do we deal with those that fail earlier? If we consider 2 months is the life then potentially we are changing our asset early when it is still perfectly functional. We can’t attribute a “life” in this case, as the assets do not fail at or around the same time so they subscribe to one of the random failure patterns.

What you may be interested to note is that the largest percentage of assets at around 68% have an increased risk of infant mortality or more plainly of failing shortly after entry into service (pattern F in the earlier diagram).  Compare this to a more traditional view of how assets fail (pattern A – showing a defined wear out zone after a period of time) representing around 4% of assets and you can see that treating all of your assets as if they wear out can actually increase the risk of asset failure where the asset has a high infant mortality.

Hang on a minute – are you saying that most of my assets can fail anytime and there is nothing I can do about it?? Pretty much (to the first point) and of course there is (to the second) but then we would need to Segway into a conversation around criticality and how we design systems to mitigate risk of failure and that is for a future date. However the first step is to understand that assets perform differently and that some do not have a “life” as such - as grasping this concept will inform the approach to managing your varied asset portfolio.

One other concept to grasp is that context is everything – not all assets of the same type will be treated the same as by managing your assets you are seeking to mitigate the consequences of their failure and these will differ in many cases (but more on this is in a later post).

Until next time ;).