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Posts tagged ‘GUM’

ISO FDIS 17025:2017 – Impacts on accredited laboratories

ISO FDIS 17025:2017 – Impacts on accredited laboratories

As noted in my previous article on the final draft international standard FDIS 17025:2017 (https://consultglp.com/2017/10/30/iso-fdis-170252017-sampling-sampling-uncertainty/ ), the current ISO/IEC 17025:2005 version widely used by accredited laboratories around the world will soon be replaced by this new standard, expected to be published very soon.

The ILAC (International Laboratory Accreditation Cooperation), a formal cooperation to promote establishing an international arrangement between member accreditation bodies based on peer evaluation and mutual acceptance with a view to develop and harmonize laboratory and inspection body accreditation practices, has recommended a 3-year transition to fully implement this new standard from the date of its publication. At the end of the transition period, laboratories not accredited to the ISO/IEC 17025:2017 will not be allowed to issue endorsed test or calibration reports and will not be recognized under the ILAC MRA terms.

Today, there are over 90 member accreditation bodies from over 80 economies have signed the ILAC Mutual Recognition Arrangement (ILAC MRA). This new ISO standard therefore has a tremendous impact on all accredited calibration and testing laboratories of which their national accreditation bodies are signatory members of the ILAC MRA.

Each national accreditation body is expected to work out its own transition plan with actions to be taken to help the laboratories under its charge to smoothly migrate to the new practices. These actions might include, but not limit to, effective communication, scheduled seminars/training courses for laboratory managers and technical assessors, and mapping out a time table and policies to achieve the ultimate goal.

In the nutshell, the new standard has standardized and aligned its structure and contents with other recently revised ISO standards, and the ISO 9001:2015, in particular. It reinforces a process-based model and focuses on outcomes rather than prescriptive requirements such as the absence of familiar terms like quality manual, quality manager, etc. and giving less description on other documentation. It will allow more flexibility for laboratory operation as long as the laboratory’s technical competence can be assessed and recognized by the standard.

The following notes highlight major significant changes in the new revision as compared with those in the 2005 version:

  1. Standard format

Many requirements under the 2005 version remain unchanged but appear in different places of the document, under headlines like general requirements (Clause 4), structural requirements (Clause 5), resource requirements (Clause 6), process requirements (Clause 7) and management system requirements (Clause 8). Also, there are certain language updates to reflect the current standard practices and technologies.

  1. Laboratory activities

Under Clause 3 on Terms and Definitions, the term “laboratory activities” in sub-clause 3.6 has included “sampling, associated with subsequent testing or calibration” in addition to the existing “testing” and “calibration” activities. This is a major scope expansion of the laboratory activity for accreditation and will be a challenge for most testing laboratories which are engaged in field sampling. Sub-sampling of test sample in a laboratory prior to analysis is considered to be part of the test procedure.

  1. Risk-based thinking

The revision has incorporated a new “risk-based thinking” which requires the laboratory to plan and implement actions to address possible risks and opportunities associated with the laboratory activities. The laboratory is responsible for deciding which risks and opportunities need to be addressed. The aims are to:

a) give assurance that the management system achieves its intended results;

b) enhance opportunities to achieve the purpose and objectives of the laboratory;

c) prevent, or minimize, undesired elements

The word of ‘risk’ can be found in the following requirements:

Clause 4.1.4:   Identifying risk to impartiality

Clause 7.8.6.1:  “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.”

Clause 7.10:  Actions taken for nonconforming work based upon risk levels established by the laboratory

Clause 8.5:   Actions to address risks and opportunities

Clause 8.7:   Updated risk and opportunities when corrective action is taken

Clause 8.9:   Management review agenda to include results of risk identification

  1. Impartiality

The new standard has stressed on the laboratory’s impartiality.  Under Clause 4 General Requirements, the Sub-clause 4.1 requires the laboratory to identify risks to its impartiality on an on-going basis and if a risk to impartiality is identified, the laboratory shall be able to demonstrate how it will eliminate or minimize such risk.

  1. Decision rule

The term “decision rule” is new to this ISO standard. It first appears in Clause 3.7 under Terms and Definitions which states that “rule that describes how measurement uncertainty is accounted for when stating conformity with a specified requirement”. This is in relation to Sub-clause 7.8.6 on providing “Reporting statements of conformity”.

Before the laboratory provides any statement of conformity to a specification, it is required  to first assess the level of risk (such as false acceptance, false rejection and statistical assumptions) involved in the decision rule employed which has to be documented.  See Sub-clause 7.8.6.1.

  1. External provided products and services

The new standard combines current Sub-contracting, Supplies and External Services which affect laboratory’s activities under a new headline with requirements, controls and communication guidance given under Sub-clause 6.6

  1. Evaluation of measurement uncertainty (MU)

Clause 7.6.1 requires laboratories to identify the contributions to measurement uncertainty. When evaluating MU, all contributions which are of significance, including those arising from sampling, shall be taken into account using appropriate methods of analysis.

The standard in its Clause 7.6.3 Note 3 states that “For further information, see ISO/IEC Guide 98-3, ISO 5725 and ISO 21748”.  It is inferred that the laboratory has a choice in the MU evaluation methods, i.e. using either the conventional GUM (bottom up) or the holistic method performance (top down) approaches can be applied in the MU evaluation.

  1.   Options in management system requirements

The new standard allows the laboratory to implement a management system in accordance with Option A or Option B after meeting the requirements of Sub-clauses 4 to 7.

Option A asks the laboratory to address all its sub-clauses 8.2 to 8.9 as the minimum requirements, and Option B is for a laboratory which has already established and is maintaining a management system in accordance with the requirements of ISO 9001, and which is capable of supporting and demonstrating the consistent fulfillment of the requirement of Clauses 4 to 7, whilst fulfilling at least the intent of the management system requirements specified in Sub-clauses 8.2 to 8.9.

In conclusion, in addition to aligning with the other current international standards in its structural forms and wordings, the new version of ISO 17025 to be implemented introduces new laboratory activity scope on sampling and new requirements such as risks and opportunities, decision rule, sampling uncertainty and two management system options.

Laboratories will need to acquire new skills in carrying out risk assessment, making decision rule, evaluating sampling uncertainty and learning how to incorporate this uncertainty into the overall measurement uncertainty evaluation.

Now, accredited laboratories await for their respective national accreditation body to provide new laboratory accreditation guidelines and directives in this significant migration of ISO/IEC 17025 standards from the existing 2005 version to the latest one during this 3-year transition period.

Comparing GUM and top down approaches (PDF)

Comparing GUM and top down approaches

Measurement Uncertainty – Comparing GUM and top down approaches

Measurement Uncertainty – Comparing the GUM and ‘top down’ approaches

Upon requests, I tabulate the differences and advantages / disadvantages of the two broad approaches in measurement uncertainty (MU) evaluation processes for easier appreciation.

GUM (bottom up) approach

Top down approaches

 

Component-by-component using Gauss’ error propagation law for uncorrelated errors

 

Component-by-component using Gauss’ error propagation law for uncorrelated errors

Which components?

Studying uncertainty contributions in    each step of test method as much as possible

 

Which components?

Using repeatability, reproducibility and trueness of test method, according to basic principle: accuracy = trueness (estimates of bias) + precision (estimates of random variability)

“Modeling approach” or “bottom up approach”, based on a comprehensive mathematical model of the measurement procedure, evaluating individual uncertainty contribution as dedicated input quantities “Empirical approach” or “top up approach”, based on whole method performance to comprise the effects from as many relevant uncertainty sources as possible using the method bias and precision data. Such approaches are fully in compliant with the GUM, provided that the GUM principles are observed.
 

Acknowledged as the master document on the subject of  measurement uncertainty

 

There are few alternative top down approaches, receiving greater attention by global testing community today

 

GUM classifies uncertainty components according to their method of determination into type A and type B:

Type A – obtained by statistical analysis

Type B – obtained by means other than statistical analysis, such as transforming a given uncertainty (e.g. CRM) or past experience

 

 

 

Top down approaches consider mainly Type A data from own statistical analysis from within-lab method validation and inter-laboratory comparison studies

 

 

GUM assumes that systematic errors are either eliminated by technical means or corrected by calculation.

 

 

The top down approaches allow for method bias in uncertainty budget
 

 

 

In GUM, when calculating the combined standard uncertainty of the final test result, all uncertainty components are treated equally

 

The top down approach strategy combines the use of existing data from validation studies with the flexibility of additional model-based evaluation of individual residual effect uncertainty contributions.

Advantages:

1.   Demanding critical assessment and full understanding of the analytical steps in a test method

2.   Consistent with other fields of measurements such as calibration

3.   The MU result generated is relevant to the particular laboratory that produces it

 

 

 

 

 

Advantages:

1.   Quality data from method validation and inter-lab comparison studies are readily available in a well run accredited laboratory

2.   Very much simpler process in MU evaluation

3.   The MU data of a test method is dynamic and current, due to using existing and experimentally determined quality control checks and method validation results

4.   This approach is based on statistical analysis of data generated in intra- and inter-laboratory collaborative studies on the use of a method to analyze a diversity of sample matrices.

 

Disadvantages:

1.   The GUM approach process is tedious and time consuming

2.   This methodology may underestimate the measurement uncertainty, partly because it is hard to include all possible uncertainty contributions

3.   GUM may unrealistically assume certain errors are random (i.e. normally distributed) and independent

4.   GUM provides a broad indication of the possible level of uncertainty associated with the method rather than a measurement.

5.   It does not take into account either matrix-associated errors or the actual day-to-day variation seen in a laboratory

6.   GUM does not apply well when there is no mathematical model in the test method

Disadvantages:

1.   The top down approach may not by itself identify where the major errors could be occurring in process and the results generated are the products of technical competence of the laboratory concerned

2.   That inter-lab reproducibility data considered in certain instances may not be fully representative for variability of results on actual samples, unless it is standardized

 

 

 

 

 

Monte Carlo method – an alternative GUM approach for measurement uncertainty evaluation

Monte Carlo method – Basic idea

Is an expanded uncertainty U synonym to a confident limit?

Is an expanded uncertainty synonym to a confidence limit