Our Meetup.com website has now got 16 members registered for Interest Group in Measurement Uncertainty for Test Labs since its formation on August 4 to foster fellowship and interaction on how to implement this important requirement in the ISO/IEC 17025 laboratory accreditation standards. New members are most welcome. Click http://www.meetup.com/Interest-Group-in-Measurement-Uncertainty-for-test-labs/
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Which alternative top down MU method will work best for you?
There are several alternative top down methods available for the estimation of measurement uncertainty (MU) in chemical and microbiological laboratories. One or two will work best under your laboratory conditions.
All accredited laboratories would have implemented a robust laboratory quality management system in accordance to the ISO/IEC 17025 standards. In this scenario, you would have carried out certain method validation and verification on your in-house test methods and standard/official methods, respectively. You would also have consistently been running laboratory control samples (LCS’s) as and when you conduct a batch of sample analysis to monitor the accuracy of your test results. Similarly, you should also have been participating some proficiency testing (PT) programs at regular intervals as required by the national accreditation body.
With this in mind, I recommend the following top down approaches which will be suitable for your MU evaluation:
- For established standard test methods (like ISO, AOCS, BS, EN, ASTM, etc.) that you have been running routinely with readily available QC data, the use of data repeatability, reproducibility and trueness estimates will be fine for estimating the MU, such as following the ISO 21748:2010;
- If you have been using stable laboratory control samples (LCS’s) to monitor your test accuracy regularly, you can consider plotting the LCS data on a Shewhart control chart against time and apply the variance of the data moving average as the estimation of its standard uncertainty (see ASTM D6299-08). Certain pre-requisites however, do apply here, such as statistically confirming your QC data are completely random and independent by the Anderson-Darling (AD) or Shapiro-Wilk tests for normality, and visually checking the data trend of the Shewhart chart to follow a set of chart rules laid down by the standards;
- If your laboratory is not able to take part in any PT program because there is no such program to check your test parameters, you can use your within-lab reproducibility (or intermediate precision) data and the result bias estimates which are available in your method validation process. The relevant reference of this approach is ISO 11352:2012;
- For certain types of chemical tests involving a series of certified reference materials as calibration standards (e.g. the determination of total sulphur in petroleum product by X-ray fluorescence spectrometric method – ASTM D4294 – which is a direct read-out from the energy-dispersive X-ray fluorescence sulphur meter with 4-point or 5-point calibration using different sulphur reference standards), the laboratory concerned can plot a linear calibration curve involving the actual test results of these reference standards against the assigned reference values to estimate the uncertainty. See reference ISO 11095:1996(2012).
- The GUM component-by-component method is not suitable for the MU estimation of microbiological count experiment because the distribution of such data is not strictly normal whilst GUM has made this assumption. In fact, the Poisson probability distribution is better in this situation. The MU estimation for microbiological counting therefore is based on the holistic performance of the test method and we need to make logarithmic transformation of the within-lab reproducibility data before evaluating its variances. Various established documents are available for reference, such as ISO 10936:2006, BS 8496:2007, A2LA G108, NMKL Procedure No. 8, etc.
In my opinion, the ISO 11095 method in (d) is the most difficult one for a laboratory analyst who has acquired only elementary statistical skills, because of its application of more complicated statistical tools in estimating the constant and proportional variances. The other approaches are quite straight forward and will be easily appreciated by the analysts with average statistical knowledge.
A list of published international documents in relation to the use of top down MU approaches (not exhaustive)
- ISO 21748:2010 Guidance for the use of repeatability, reproducibility and trueness estimates in measurement uncertainty estimation
- ISO 11095:1996 (2012) Linear calibration using reference materials
- ISO 11352:2012 Water quality — Estimation of measurement uncertainty based on validation and quality control data
- ISO 19036:2006 Microbiology of food and animal feeding stuffs — Guidelines for the estimation of measurement uncertainty for quantitative determinations Amd1:2009: Measurement uncertainty for low counts
- ISO 29201:2012 Water Quality – The variability of test results and the uncertainty of measurement of microbiological enumeration methods
- ISO Guide 98-3/Suppl. 1 Uncertainty of measurement Part 3: Guide to the expression of uncertainty of measurement Supplement 1 : Propagation of distributions using a Monte Carlo method
- BS 8496:2007 Water quality. Enumeration of micro-organisms in water samples
- ASTM D2554-07 Estimating and monitoring the uncertainty of test results of a test method in a single laboratory using a control sample program
- ASTM D6299-08 Applying statistical quality assurance and control charting techniques to evaluate analytical measurement system performance
- ASTM E2093-05 Optimizing controlling and reporting test method uncertainty from multiple workstations in the same laboratory organization
- EuroLab Technical Report No. 1/2006 Guide to the Evaluation of Measurement Uncertainty for Quantitative Test Results
- NORDIC Technical Report TR 537 Edition 3.1 Handbook for Calculation of Measurement Uncertainty in Environmental Laboratories
- A2LA G108 – Guidelines for Estimating Uncertainty for Microbiological Counting Methods
- NMKL Procedure No. 8 (2002) Measurement of uncertainty in microbiological examination of foods.
- CNAS-GL34:2013 基于质控数据环境检测测量不确定度评定指南 Guidance for measurement uncertainty evaluation based on quality control data in environmental testing
Yeoh GH of GLP Consulting has at the http://www.meetup.com website set up a chat group, namely Interest Group in Measurement Uncertainty for Test Labs for better interaction with the laboratory and QA personnel in this region.
The very first Meetup session is scheduled on August 30 in Singapore with venue to be confirmed later. All are welcome to join this interest group at https://www.meetup.com/Interest-Group-in-Measurement-Uncertainty-for-Test-Labs/ even though you might not be in Singapore as we shall post summaries of discussions and useful pointers after the meetup.