Instrumentation & Measurement Magazine 23-2 - 82

Why Smart Metrology is
No Longer Optional
Jean-Michel Pou and Laurent Leblond

S

mart Metrology is the subject of a work we wrote
and published with the Association Française de
Normalisation (AFNOR, French Standardization
Association) in 2016 [1]. In this new work, we offer a very different vision of the role of metrology in industry from the
traditional view, which tends to focus on the management of
a stock of measuring instruments. The emergence of Big Data
and Artificial Intelligence algorithms has caused us to rethink
the role of the metrologist: while the job of auditors has more
or less been to stick approval labels on instruments. Big Data,
by definition, requires reliable data to produce meaningful results. This article sets out to explain why the metrology we are
familiar with has been acceptable until now, and why it has become so important to change our approach so as to concentrate
on improving performance and managing resources more efficiently. This article is the translation of the article "Pourquoi la
Smart Metrology n'est plus une option" that has been published,
in French, in the blog www.smart-metrology.com [2].

Background
We live in a world where measurement uncertainty simply
does not exist! The very function of Legal Metrology, back in
1836, was to remove ambiguity from commercial transactions
and establish trust in the measurements used to set sale prices.
Since the Eve of the French Revolution, measurements have
been taken to be "accurate," and continue to be so today.
We all understand and use measurement results without
worrying about the inevitable associated uncertainties. This
is not a problem in commercial transactions, but it is a mistake to take the same attitude in an industrial context. While it
is easy to understand why measurement uncertainties might
be considered negligible in a commercial environment, it is
somewhat surprising to see that same laxity allowed to affect
industrial decision-making.
With commercial transactions, a measurement error may
be in favor of either buyer or seller (with a corresponding loss
for the other party, whichever that may be). There may be a
little more or a little less petrol in the tank, a little more or a little less weight of tomato in the shopping bag, but it does not
82	

matter as long as the difference between measurement and reality remains reasonable... no one is going to die!
In industrial decision-making, on the other hand, the situation is different. The measurement error is just as impartial, of
course. It can be the source of what we call Customer Risk (the
belief that an entity is compliant when it is not), just as easily
as Supplier Risk (where an entity is declared non-compliant
when in fact it is compliant). Imagine, for a moment, a situation
that involves you, for example, a medical laboratory test. A
measurement error might lead to the belief that you are not ill
when in reality you are. You therefore do not receive the treatment you need to improve your condition, or perhaps even
save your life. Or think of a critical component in an airplane
engine that has been labelled compliant when in reality it is
not... imagine being on that plane! Unlike commercial transactions, industrial decisions can, potentially, be fatal! These
analogies should make the true significance of "customer risk"
very clear.
The notion of "supplier risk" may have a certain appeal,
suggesting as it does the idea of "risk-sharing," but the reality
is somewhat more subtle. To go back to the biomedical example, "supplier risk" would be to mistakenly declare a healthy
person to be ill. That perfectly healthy person might, as a result
of a measurement error, needlessly undergo chemotherapy!
Can one really talk of a "supplier risk" when it is the patient
(i.e., the customer) who has to suffer the consequences? In fact,
is this ever not the case? When a verification process wrongly
finds a device to be non-compliant, is it really the supplier (i.e.,
the laboratory that has established the non-conformity) that
suffers the consequences of the error, or the customer? Anyone who has been through an impact study, anyone who has
replaced a supposedly non-compliant device as a matter of
urgency, knows that it is they who have paid for an error of
judgment, quite literally, and possibly at an exorbitant rate,
not the supplier.
Moreover, it has been demonstrated that the relationship between the two risks is not symmetrical: a gain of 1%
on one side can generate a loss of 10% or more on the other.
When it becomes apparent that both risks are borne by the

IEEE Instrumentation & Measurement Magazine	
1094-6969/20/$25.00©2020IEEE

April 2020


http://www.smart-metrology.com

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