### Basis of decision rule on conformity testing

There are three fundamental types of risks associated with the uncertainty approach through making conformity or compliance decisions for tests which are based on meeting specification interval or regulatory limits. Conformity decision rules can then be applied accordingly.

In summary, they are:

- Risk of false acceptance of a test result
- Risk of false rejection of a test result
- Shared risk

The basis of the decision rule
is to determine an “*Acceptance zone*”
and a “*Rejection zone*”, such that if
the measurement result lies in the acceptance zone, the product is declared
compliant, and, if it is in the rejection zone, it is declared
non-compliant. Hence, a decision rule
documents the method of determining the location of acceptance and rejection
zones, ideally including the minimum acceptable level of the probability that
the value of the targeted analyte lies within the specification limits.

A straight forward decision
rule that is widely used today is in a situation where a measurement implies
non-compliance with an upper or lower specification limit if the measured value
exceeds the limit by its expanded uncertainty, *U*.

By adopting this approach, it
should be emphasized that it is based on an assumption that the uncertainty of
measurement is represented by a normal or Gaussian probability distribution
function (PDF), which is consistent with the typical measurement results (being
assumed the applicability of the Central Limit Theorem),

**Current
practices**

When
performing a measurement and subsequently making a statement of conformity, for
example*, in or out-of-specification *to manufacturer’s specifications or *Pass/Fail*
to a particular requirement, there can be only two possible outcomes:

*The result is reported as conforming with the specification**The result is reported as not conforming with the specification*

Currently, the decision rule is often based on direct comparison of measurement value with the specification or regulatory limits. So, when the test result is found to be exactly on the dot of the specification, we would gladly state its conformity with the specification. The reason can be that these limits are deemed to have taken into account the measurement uncertainty (which is not normally true) or it has been assumed that the laboratory’s measurement value has ** zero uncertainty**! But, by realizing the fact that there is always a presence of uncertainty in all measurements, we are actually taking a 50% risk to have the actual or true value of the test parameter found outside the specification. Do we really want to undertake such a high risky reporting? If not, how are we going to minimize our exposed risk in making such statement?

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