INCOLAB – DK activities

1. INCOLAB – DK activities SC 3 meeting Prague, Czech Republic 5 December 2003

2. INCOLAB - DK • The LVD organisation in DK Ministry of Science,Techn. and Education Ministry of Industry and Economy NMI:DANIAmet Accr. body:DANAK Notified Body:Electricity Council Market surveillance Accr. test lab: Demko-UL Accr. cal labs:Arepa Accr. test (IT):Delta Authorisation Based on accreditation 6406 HDJ

3. Activities – June-November 2003 • WP0: • SC2 Meeting, June • Further contacts to labs and organisations • Visit by Slovenian partner with laboratory visits • WP4: • Guideline development • writing in progress • discussions with Dutch partner • Discussions on examples (BTC, EMC and glow-wire) • Abstract for Prague conference 6406 HDJ

4. Economic status • Costs so far: 6406 HDJ

5. WP4 - Guide • Content • Introduction – including the discussion of the inherent “method uncertainty” non-uniqueness of standards • The “Why uncertainty” • Basic GUM philosophy and practice • Model-building • Generic models for basic measurements • Uncertainty of a calibration curve • Statistical treatment of test data and their relation to GUM • Documentation of uncertainty budgets • Examples 6406 HDJ

6. Uncertainty in testing • Aim of the work: To put together a guide for practical uncertainty estimation in testing • Several documents exists (EA, A2LA, …), but they never seem to ”get down to business” • Quick to point to the general obstacle: • Standards for testing allow the implementation of tests to vary to such a degree, that ”method uncertainties” dominate – direct comparability of results is difficult • Also “GUM is difficult, so why bother…” • Many rely only on repeatability and reproducibility • and biases revealed from comparisons… 6406 HDJ

7. Beware! • All repeatability and reproducibility studies only give information on random effects! Hence are information of the measurement process. • Only a detailed (physical) examination of the measurand and measurement method may uncover sources for systematic effects. Also • Uncertainty relates to a measurement result, and a quantative test result should be treated as such. • One requirement is a well-defined measurand (well-defined test conditions) … and this often not given in a test standard. 6406 HDJ

8. Technical contents • Summary GUM method • Main difficulty of users is setting up the appropriate model function (relation between input quantities and the output quantity(ies)) • Hence, present a ”toolbox” of generic measurement methods: • Direct reading from a calibrated instrument • Substitution/transfer measurements • Balance/difference measurements, … and the often used • Generation and use of calibration curves 6406 HDJ

9. Calibration curves • Given calibration data: applied stimuli {xi , u(xi)} and measured responses {yi , u(yi)} and an empiric or physical bond f(x,y) = 0 • Find for a measured response y with u(y), the corresponding stimuli x and associated u(x). y x 6406 HDJ

10. Trueness and precision • On statistical treatment of test series trails: • Precision ~ repeatability and reproducibility • A measure for the ability of the lab to generate consistent results • Can be estimated from internal sources • Trueness ~ bias • A measure for the ability of the lab to generate correct results • Must be estimated from external sources (e.g. reference materials) 6406 HDJ

11. Practical guide • Documentation; especially important for comparability • The better the measurand is specified, the higher the comparability between results. • The assumptions of the measurement model and the uncertainty contributions are the key, and should be detailed. • And examples … • Heating in Black Test Corner • Glow wire • EMC • … 6406 HDJ