You’ve walking to your car late one night and drop your keys. You look under the street light but don’t see them there. Is it now safe to assume that your keys no longer exist? Of course not! Rather, you understand the limits of street lighting and whip out your phone for a portable light source. Ah, there they are!
How many of you have been underwhelmed by the introduction of a new condition monitoring technology that promised great results, but failed to deliver? I’ve witnessed too many cases of Con Mon that are highly technically-focused, but weak from a business-perspective. A CM technician thinks it’s a great idea to get an extra 20 % life from a hydraulic cylinder until the maintenance planner reminds him that the asset needs to come in earlier for major maintenance. Any potential cost benefit from component life extension is swamped by downtime-related losses when replaced as an ad-hoc event.
When introducing a Con Mon strategy and technique, RCM reminds us to always think first about the process function and what degraded performance looks like. Next, we need to consider likely failure modes and discover if there are ways to detect the on-set of failure. If there is a reliable way to measure this loss of function and if it fails in a gradual way, then Con Mon could be used as part of a condition-based maintenance strategy. The different technologies (thermal, vibration, oil analysis) are used to provide progressively earlier warnings, placing the identification of a defect on different points of the “P-F curve”. The earlier we find an indicator, the more notice we have to plan and perform corrective maintenance. However, like medical imaging, we need to interpret data and we can never be 100% certain about what is presented to us. If there is a strong relationship between the early warning signs and if the progress towards functional failure happens gradually, the Con Mon technology can be very useful.
Now, I’m not sure whether you noticed the series of “ifs” in the previous paragraph. If not, let me expound upon them. Each one of these indicates a limit to the use of the condition monitoring strategy or instrument. Each “if” places a condition on the range or precision of any measurements taken; factors that can limit the ability to know actual asset condition. Add to these conditions the earlier technical versus business focus issue and we begin to see just how easy it can be to question the usefulness of condition monitoring.
Don’t get me wrong, I am in awe of good Condition Monitoring practitioners. They walk a very fine line that separates the alter egos of Chicken Little and Evel Knievel. Too cautious and no significant gain is made in component life. Too adventurous and all of the benefits accrued are flushed down the tubes of an asset breakdown. Good CM people never assume an outcome from a measure, attempting to shoehorn measures to fit a preconceived pattern. They know and respect the limits of technology, calibrate their understanding and always act rationally.
These limits on the use of Condition Monitoring techniques reminds me of a similar debate that I recently read regarding a famous quote by Richard Dawkins in his first work, The Selfish Gene. He writes: “[Genes] swarm in huge colonies, safe inside gigantic lumbering robots, sealed off from the outside world, communicating with it by tortuous indirect routes, manipulating it by remote control. They are in you and me; they created us, body and mind; and their preservation is the ultimate rationale for our existence.”
We see here a powerful and influential interpretation of a basic scientific concept – biological evolution. However, can we be sure that these strongly interpretative statements are themselves actually scientific? Has Dawkins realised and respected the limits of scientific understanding or is he hoodwinking himself by an a priori commitment to a particular truth claim?
To appreciate the issue, consider the following rewriting of this paragraph by the celebrated Oxford physiologist and systems biologist Denis Noble. What is proven empirical fact has been retained; what is interpretative has been changed, this time offering a somewhat different interpretation.
“[Genes] are trapped in huge colonies, locked inside highly intelligent beings, moulded by the outside world, communicating with it by complex processes, through which, blindly, as if by magic, function emerges. They are in you and me; we are the system that allows their code to be read; and their preservation is totally dependent on the joy that we experience in reproducing ourselves. We are the ultimate rationale for their existence.”
Dawkins and Noble see things in completely different ways. They cannot both be right. Both smuggle in a series of quite different value judgements and metaphysical statements, yet their statements are ‘empirically equivalent’. In other words, they both have equally good grounding in observation and experimental evidence. So, which is right? Which is more scientific? How could we decide which is to be preferred on scientific grounds? As Noble observes—and Dawkins concurs—‘no-one seems to be able to think of an experiment that would detect an empirical difference between them’.
Whether deciding on the maintenance of a hydraulic cylinder or an aspect of our personal life, we must always be aware of the limits of the tool, technology or discipline we attempt to employ. Rather than allowing our bias and prejudice to reign, it’s important to come to every problem and uncertainty with an open mind and be prepared to follow the evidence where it leads. Otherwise, we might be letting Chicken Little ride a motorcycle over the Grand Canyons of our thinking and I can’t see that ending well!
 The Dawkins Delusion by Alister McGrath, Pg 15