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An Introduction to Quality Assurance in Analytical Science

An Introduction to Quality Assurance in Analytical Science. Dr Irene Mueller-Harvey Mr Richard Baker Mr Brian Woodget. Part 5 - Expression of Results. Contents: Validation, traceability and measurement uncertainty (slides 3,4) The ‘what’, ‘why’ and ‘how’ of measurement

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An Introduction to Quality Assurance in Analytical Science

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  1. An Introduction to Quality Assurance in Analytical Science Dr Irene Mueller-Harvey Mr Richard Baker Mr Brian Woodget

  2. Part 5 - Expression of Results • Contents: • Validation, traceability and measurement • uncertainty (slides 3,4) • The ‘what’, ‘why’ and ‘how’ of measurement • uncertainty (slides 5-15) • Reporting results (slide 16,17) The presentation contains some animation which will be activated automatically (no more than a 2 second delay), by mouse click or by use of the ‘page down’ key on your keyboard.

  3. The Famous Trio: When expressing results of analytical measurements you will need to bear in mind the 3 inter-linking parameters of: Will the results be traceable to an accepted reference standard? Has the method been validated and it is fit for purpose? VALIDATION TRACEABILITY How sure will you be of the accuracy of the results obtained? MEASUREMENT UNCERTAINTY

  4. About validation, traceability & measurement uncertainty As you have seen in Part 1 of this presentation, all analytical results have an error associated with them. Measurement uncertainty is an estimate of the potential size of that error and is affected by both the time and effort put into method validation and the traceability of standard reference materials and substances Note: refer to Part 2 of the presentation for a description of method validation and to Part 3 for a description of traceability

  5. Measurement Uncertainty (1) Analysis of a sample of soil has shown it to contain 30 + 5 mg/kg of lead Mean result from replicate analyses Estimate of the measurement uncertainty You need to consider from where the uncertainty is likely to arise Note: accredited laboratories (ISO 17025) carrying out this analysis would need to be aware of the levels of uncertainty but would not necessarily have to present this data unless asked. So the result could well be presented as 30 mg/kg

  6. Measurement Uncertainty (2) Sources of uncertainty arise from ALL aspects of the analysis - these could include: sampling Volumetric glassware Calibration standards Potential sources of error instruments sample preparation operator skill

  7. MeasurementUncertainty (3) Analytical balance • To estimate the measure of overall uncertainty, errors likely to occur in all aspects of the analysis need to be taken into account in the form of individual standard deviations (SD). Data may be obtained from: • manufacturers of equipment and reagents (e.g. balances, • volumetric glassware, standard reagents etc) • data from method validation • estimates from the literature or from previous experience An overall estimate of the uncertainty can then be calculated by using accepted procedures.

  8. MeasurementUncertainty (3a) The accuracy of an analytical balance is fundamental to all of the procedures carried out within an analytical laboratory. The balance should be capable of weighing accurately to + 0.1 mg and is the starting point for most measurements (sample weight, preparation of standards, method validation etc.) The balance must be calibrated periodically against weights traceable to the UK standard held at the National Physical Laboratory (NPL), and checked at least every day against a set of weights held in the laboratory, specifically for this purpose. All calibration data must be stored.

  9. Measurementuncertainty (4) The uncertainty estimation process can be illustrated diagrammatically: SPECIFICATION - clear statement of what is being measured and the relationship between it and parameters on which it depends IDENTIFY UNCERTAINTYSOURCES - list sources for each part of the process or for each parameter QUANTIFY UNCERTAINTYCOMPONENTS - estimate the size of each uncertainty component CONVERT TO STANDARDDEVIATIONS - express error component as a standard deviation CALCULATE THE COMBINED UNCERTAINTY RE-EVALUATE THE PROCESS IF NECESSARY

  10. Measurementuncertainty (5) Standard uncertainties A measure of the SD of an uncertainty component [u(y)] - may be calculated from: • experimental data • accuracy guaranteed by a piece of equipment • e.g. balance accurate to + 0.1 mg @ 95% confidence • which may be converted to a SD • pipette guaranteed to deliver 25 + 0.2 ml. Although no • confidence level has been stated, SD may again be • calculated.

  11. Measurementuncertainty (6) Combined uncertainties Dependent upon the type of analysis carried out, the standard uncertainties may be combined to produce a combined uncertainty [uc(y)] One of three equations may be used, the choice being dependent upon the complexity of the analysis and the relationship between the components parts A model equation must be devised which describes in simple algebraic terms the whole analysis process

  12. Measurementuncertainty (7) The rules for estimating combined uncertainties depend upon the model algebraic equation devised to illustrate the analysis process. You only need consider two at the present time: Rule 1 - for models involving only a sum or difference of quantities eg. For y = a + b + c, the combined uncertainty is given by: [uc(y)]2 = u(a)2 + u(b)2 + u(c)2 Rule 2 - for models involving only a product or a quotient eg: For y = a.b.c or y = a/(b.c) , the combined uncertainty is given by: [uc(y)/y]2 = [u(a)/a]2 + [u(b)/b]2 + [u(c)/c]2

  13. Measurementuncertainty (7a) Total mass (T) is given by: T = a + b + c + d = 27.81 + 32.45 + 46.10 + 19.01 = 125.37 [uc(T)]2 = u(a)2 + u(b)2 + u(c)2 + u(d)2 = 0.012 + 0.022 + 0.082 + 0.022 = 0.0073 uc(T) =+ 0.085 Thus: T = 125.37 + 0.085 Example to illustrate a calculation involving rule 1 Suppose that you have four components (a, b, c, d) and you need to know their combined mass and the uncertainty associated with this mass. The following information is available: a = 27.81 g, u(a) = + 0.01 g; b = 32.45 g, u(b) = + 0.02 g c = 46.10 g, u(c) = + 0.08 g d = 19.01 g, u(d) = + 0.02 g

  14. The equation for the calculation may be expressed as: CKOH X VKOH CHCl = = 0.1011 VHCl Each of the individual standard uncertainties needs to be expressed as an RSD so for: CKOH = 0.00017/0.0990 = 0.00172 VKOH = 0.032/25.54 = 0.00125 VHCL = 0.021/25.00 = 0.00084 Thus: uc(CHCl) =[(0.00172)2+ (0.00125)2 + (0.00084)2]1/2 X 0.1011 uc(CHCl) = [0.0000051]1/2 X 0.1011 = 0.00226 X 0.1011 = 0.00023 M CHCl = 0.1011 + 0.0002 M Measurementuncertainty (7b) Example to illustrate a calculation involving rule 2 You have performed an acid/base titration to measure the molarity (M) of a solution of HCl, by titration with a standard solution of KOH. The following information is known or was obtained during the titration CKOH = 0.0990 M, [u(CKOH) = 0.00017] VKOH = 25.54 ml, [u(VKOH) = 0.032] VHCl = 25.00 ml, [u(VHCl) = 0.021]

  15. Measurementuncertainty (8) Coverage factor In order to give confidence to the value for the combined uncertainty, the calculated value uc(y) is often multiplied by a coverage factor (k). For a 95% level of confidence the value of k is 2 [ See Student’s ‘t’ test table] Note: a more complete description of the principles used for calculating uncertainties may be found in: “Quantifying Uncertainty in Analytical Measurements”, Eurochem, 1995. “Quality in the Analytical Laboratory”, E. Prichard (Ed), Wiley, 1995, Chapter 6.

  16. The test report of an accredited laboratory must conform to the requirements of the accreditation body - usually the report must clearly identify- Reporting results • - the laboratory • - the client • - the samples • - the date they were received • - the method of analysis • - the analyst • - the date of the report • - the unique Test Report no. on every page The report format must ensure that there can be no confusion over which results refer to which samples and it should give any information about the condition of the samples that may have affected the test results.

  17. Amiable Laboratory A UKASaccredited testing laboratory No. £$%& Benevolent Department Well-intentioned Organisation Tel: 01234 567890 Fax: 01234 567891 Test report number T02 JAN 002 Client XYZAB £$%& Test batch number mc218 Recipient's name A Client Date received 02/01/02 Date reported 09/01/02 Analyst C. Batch description 208 Raw milks Fat, Protein, Lactose by Milk-o-scan (FAL method 7.3.1) Details of analyses Method 7.3.1 is carried out in accordance with BS EN ISO/IEC 17025 standard Calibration data Typical calibration range for milk samples: Fat: 1.6 - 6.6 % Protein: 2.6 - 4.0 % Lactose: 3.8 - 5.0 % Comments 8 missing samples 51,99,100,135,138,145,164,189 . Signed Print name (authorised signatory) TEST REPORT HEADER For Accredited Tests (example for demonstration only)

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