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QUOVADIS WP 2 - A holistic approach towards quality management and classification Prof. Dr.-Ing. Sabine Flamme 14. Dec

QUOVADIS WP 2 - A holistic approach towards quality management and classification Prof. Dr.-Ing. Sabine Flamme 14. December 2006, Ispra. Tasks. Development of an European database on SRF production according to the classification system

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QUOVADIS WP 2 - A holistic approach towards quality management and classification Prof. Dr.-Ing. Sabine Flamme 14. Dec

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  1. QUOVADIS WP 2 - A holistic approach towards quality management and classificationProf. Dr.-Ing. Sabine Flamme14. December 2006, Ispra

  2. Tasks • Development of an European database on SRF production according to the classification system • Validation of CEN/TS on SRF classification and QM specifica-tion and classification including recommendations to TC 343 for the eventual revision of the TS before its upgrade to an European Standard (EN)

  3. Examination of European SRF-data according to the classification system (relates to CEN TC 343 WG 2) • Reply: • 90 replies towards SRFs produced in 78 plants (from 11 nations) Austria (6), Belgium (9), Denmark (1), Finland (4), Germany (21), Italy (27), The Netherlands (8), Norway (3), Sweden (7), United Kingdom (4) (in brackets: Number of replies towards SRF per nation)) France: Only one statement towards used tyres was given • very different quality: „best case“: questionnaire filled in completely, no requests necessary „worst case“: only analysis data or technical data available

  4. Previous activities • Check of the returns (examination of plausibility) and update of the questionnaires (including the results of analyses from external data bases f. e. ERFO) • Data examination with view on plausibility • Carry out calculations (if necessary, conversion from units) • Categorisation of the data quality with respect to the classification parameters (single data, n > = 40; single data, N >= 10 and < 40; single data, n < 10; no examination possible) • Examination of the classification and the classification parameters • Examination for the class distribution(class code e. g. "NCV 3, Cl 2, Hg 2")

  5. Summary of evaluable data

  6. Mercury: Compliance rules for classification Class code is established using median and 80th percentile based on • at least the last ten validated measurements or • at least ten validated measurements per annum taken at random • Prediction method for first classification: • Using the 50 % rule in case of more than ten data assays are available or • Using a random generator in case of more than 40 data assays are available 50 % rule: classification is determined by comparing the measurements results of 50 % of the class limits (median and/or 80th percentile)

  7. Mercury: Proceeding of classification In most cases insufficient database for comparison per annum INFA evaluated the median and the 80th percentile of all given assays per SRF – for the first classification • Statistical evaluation when ten or more assays were given (comparison with the half limit values) – 50 %-Rule • Furthermore evaluation via RND when 40 or more assays were given (comparison with the whole limit values)

  8. Results classification Mercury (via statistic) Statistical evaluation according to the whole database per SRF and parameter

  9. Comparison results classification Mercury (statistic vs. RND) Statistical evaluation according to the whole database per SRF and parameter Detection limits not always given

  10. NCV and Chlorine: Compliance rules for classification and proceeding Compliance rules: Comparison with the limit values of the classes has to be made by the mean of the values of • at least the last ten validated measurements or • at least ten validated measurements per annum taken at random Proceeding of classification: In most cases insufficient database for comparison per annum • INFA evaluated the mean of all given assays per SRF • Statistical evaluation when ten or more assays were given (comparison with the whole limit values) • Additional evaluation via RND when 40 or more assays were given (comparison with the whole limit values)

  11. Results classification NCV and Chlorine (via statistic) Statistical evaluation according to the whole database per SRF and parameter

  12. Comparison results classification NCV (statistic vs. RND) Statistical evaluation according to the whole database per SRF and parameter

  13. Comparison results classification Chlorine (statistic vs. RND) Statistical evaluation according to the whole database per SRF and parameter

  14. Mercury subject to quality management system n. s. = not specified Statistical evaluation according to the whole database per SRF and parameter

  15. Mercury subject to origin of waste, the SRF were made from n. s. = not specified Statistical evaluation according to the whole database per SRF and parameter

  16. Mercury subject to use n. s. = not specified co-incineration: only co-incineration, co-incineration / incineration: co-incineration as well as incineration Statistical evaluation according to the whole database per SRF and parameter

  17. Conclusions (I) • Necessity for analytical modification: • Analytical methods for the parameters have to be harmonised (necessary for standardised estimation) • Mercury: maximum detection limits should be givend • actual state: • for each type of SRF is an adequate class available

  18. Conclusions (II) • Necessity to work prCEN/TS 15359 over (have to work out for deliverable 2.5), e. g.: • Textual modification: for NCV and Chlorine addition of a specified reference to the consideration of the 95% confidence interval; in contrast to prCEN/TR 15508 a note is missing here) • … • Further validation of the TS after its revision and after the analytical modification should be done

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