Gap in training standards – A threat?

Quality control in condition monitoring diagnostics is critical to ensure reliable analysis and advice. As a means of controlling this, the CM community has relied upon the standards community to develop a range of technical and competency standards from which the user community can select according to need.

In the area of the practitioner, there are a number of training standards and qualifications available that can be used to build contracts and to ensure that the individual experts are indeed proven and certified as such. As a result, you can demand that your provider must demonstrate their competence by using only certified data collectors, analysts and programme managers. This is true for Vibration Analysis(VA), Thermal Analysis (TA), Lubricant Analysis (LA) and Ultrasonic Analysis (UA) etc. ISO 18436 and its parts covers this.

These discreet condition monitoring technologies have evolved over the last 70 or so years from high-end sciences to user-friendly device oriented tools that can be deployed easily and widely used. However…

I am a little nervous about the future, for the following reasons.

As machinery items get fitted with ethernet cables and the ability to collect, store, distribute and process data we will start to see, via the “Internet of Things”, an exponential rise in the amount, depth and breadth of data in-feed. We will naturally want to use this to gain a greater understanding of the  performance  and condition of our valuable assets and we will apply existing trending techniques to these new data sets. Thus applying existing process techniques to new data which may not yield the value we expect.

The cylinder or silo’s of condition monitoring will continue to be valuable, but we will soon find that the vast amount of new data exists outside of these traditional areas. In addition we will be able to pull together VA+TA+LA+UA and OTHER data into holistic analytical tools and we will be looking for correlations that refer to future anomalies that we may wish to manage. Thus delivering greater sensitivity in detection and improved reaction time for asset health management.

From  CM practitioners perspective, I can tell you this is very exciting, but we will find that at the moment that we gain access to this wider field of vision, we will regress to immaturity and naivety. Naivety ,because we will be seeing things for the first time and having to learn how to make sense of these things. There could be no certificate for competence in advanced machinery data analytics. As a result, there will be no way to hold your service supplier, who may well also be the service contract holder, to account. We will have to have faith in our suppliers based upon an unverifiable claim that they are the experts in something we have already revealed is new and un-tested.

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I predict that we will experience 1) An increased level of inconsistency in reporting and decision support information and 2) An in crease in “confirmation bias” where the analyst looks for evidence to support their case – either knowingly or otherwise.

So my conclusion here is that we need to consider a broader certification system for data analytics for machinery asset health management  and we also need to remain realistic that new and exciting tools will not necessarily bring about better decision making  – it may in-fact lead to indecision.

Indecision

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