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Archive for March, 2019

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:

  1. Risk of false acceptance of a test result
  2. Risk of false rejection of a test result
  3. 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?

Decision rule and conformity testing

What is conformity testing?

Conformance testing is testing to determine whether a product, system or just a medium complies with the requirements of a product specification, contract, standard or safety regulation limit.  It refers to the issuance of a compliance statement to customers after testing.  Examples are:  Pass/Fail; Positive/Negative; On specs/Off specs, etc. 

Generally, statements of conformance are issued after testing, against a target value of the specification with a certain degree of confidence. It is usually applied in forensic, food, medical pharmaceutical, and manufacturing fields. Most QC laboratories in manufacturing industry (such as petroleum oils, foods and pharmaceutical products) and laboratories of government regulatory bodies regularly check the quality of an item against the stated specification and regulatory safety limits.

Decision rule involves measurement uncertainty

Why must measurement uncertainty be involved in the discussion of decision rule? 

To answer this, let us first be clear about the ISO definition of decision rule.  The ISO 17025:2017 clause 3.7 defines that: “Rule that describes how measurement uncertainty is accounted for when stating conformity with a specified requirement.”

Therefore, decision rule gives a prescription for the acceptance or rejection of a product based on consideration of the measurement result, its uncertainty associated, and the specification limit or limits.  Where product testing and calibration provide for reporting measured values, levels of measurement decision risk acceptable to both the customer and supplier must be prepared. Some statistical tools such as hypothesis testing covering both type I and type II errors are to be applied in decision risk assessment.

Decision rule and ISO/ IEC17025:2017

Notes on decision rule as per ISO/IEC 17025:2017 requirements


The revised ISO/IEC 17025:2017 laboratory accreditation standard introduces a new concept, i.e., “risk-based thinking” which requires the operator of an accredited laboratory to plan and implement actions to address possible risks and opportunities associated with the laboratory activities, including issuance a statement of conformity to product specification or a compliance statement against regulatory limits.

The risk-based approach to management system implementation is one in which the breadth and depth of the implementation of particular clauses is varied to best suit the perceived risk involved for that particular laboratory activity.

Indeed, the laboratory is responsible for deciding which risks and opportunities need to be addressed. The aims as stated in the ISO standard clause 8.5.1 are:

  1. to give assurance that the management system achieves its intended results;
  2. to enhance opportunities to achieve the purpose and objectives of the laboratory;
  3. to prevent, or minimize, undesired impacts or interfering elements to cause failures in the laboratory activities, and
  • to achieve improvement of the activities.

The decision rule as required in ISO/IEC 17025:2017

On the subject of decision rule for conformity testing, the word of ‘risk’ can be found in the following relevant clauses of this international standard:

Clause 7.1.3

When the customer requests a statement of conformity to a specification or standard for the test or calibration (e.g. pass/fail, in-tolerance/out-of-tolerance), the specification or standard and the decision rule shall be clearly defined.  Unless inherent in the requested specification or standard, the decision rule selected shall be communicated to, and agreed with the customer.”


When a statement of conformity to a specification or standard is provided,  the laboratory shall document the decision rule employed, taking into account the level of risk (such as false accept and false reject and statistical assumptions) associated with the decision rule employed and apply the decision rule.”


The laboratory shall report on the statement of conformity, such that the statement clearly identified:

  1.  to which results the statement of conformity applies;
  2. Which specifications, standards or part therefor are met or not met;
  3. The decision rule applied (unless it is inherent in the requested specification or standard).

From these specified requirements, it is obvious that clearly defined decision rules must be in place when the laboratory’s customer requests for inclusion of a statement of conformity on the specification in the test report after laboratory analysis.  Therefore, the tasks in front of the accredited laboratory operator are how the decision rules are going to be for a tested commodity or product, based on the laboratory’s own measurement uncertainty estimated, and how to communicate and convince the customers on its choice of reporting limits against the given specification or regulatory limits when issuing such conformity statement.