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| Puydarrieux, Stéphane; Pou, Jean Michel; Leblond, Laurent; Fischer, Nicolas; Allard, Alexandre; Feinberg, Max; El Guennouni, Driss. |
| Conformity assessment, focused on risks quantification, evolved from being binary to being probabilistic. In fact, new methods described by the standard ISO CEI guide 98-4 [1] and FD X 07-039 [2] show how measurement uncertainty is integrated in the conformity assessment (FD X 07-039 : “Role of measurement uncertainty in conformity assessment – implementation of NF ISO/IEC Guide 98-4 – illustration through industrial case studies”). In such a probabilistic framework, the conformity assessment relies on two quantities: the measurement with its related uncertainty and the measurand prior knowledge. Both quantities are combined statistically to determine measurand posterior knowledge, and to quantify a global or specific risks either for the producer or the... |
| Tipo: Text |
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| Ano: 2019 |
URL: https://archimer.ifremer.fr/doc/00693/80495/83682.pdf |
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| Allard, Alexandre; Fischer, Nicolas; Smith, Ian; Harris, Peter; Pendrill, Leslie. |
| In 2012, the Joint Committee for Guides in Metrology (JCGM) published novel guidance on the consideration of measurement uncertainty for decision-making in conformity assessment (JCGM 106:2012). The two situations of making a wrong decision are considered: the risk of accepting a non-conforming item, denoted as the customer risk, and the risk of rejecting a conforming item, denoted as the producer risk. In 2017, the revision of ISO 17025 obliged calibration and testing laboratories to “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” in the context of the decision made about the conformity of... |
| Tipo: Text |
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| Ano: 2019 |
URL: https://archimer.ifremer.fr/doc/00693/80494/83681.pdf |
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| Desenfant, Michèle; Allard, Alexandre; Lalère, Béatrice; Lardy-fontan, Sophie; Le Diouron, Véronique; Lepot, Bénédicte; Ziegler, Eric. |
| Proficiency Testing (PT) uses interlaboratory comparisons to evaluate the performance of participants for tests or measurements. The statistical design and analytical techniques applied must be appropriate for the stated purpose of each PT. Most PT schemes compare the participant’s deviation from an assigned value with a numerical criterion. Different scoring strategies are available and commonly used, as described in the International Standard ISO 13528, with a new version scheduled for publication at the end of 2015. The different strategies used to determine the assigned value and the criterion to calculate performance statistics are critical because they will lead to different interpretations. It is very important to consider whether the assigned value... |
| Tipo: Text |
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| Ano: 2015 |
URL: https://archimer.ifremer.fr/doc/00693/80492/83679.pdf |
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| Allard, Alexandre; Amarouche, Soraya. |
| esting laboratories are more and more concerned with the characterization of their measurement processes. In particular, the standard ISO 17025[2] requires the accredited laboratories to participate to interlaboratory comparisons to evaluate their proficiency to realize the measurement. Different statistical methods are available to exploit the results of this type of comparisons. In our study, first we have evaluated the reference value and the proficiency standard deviation with ISO 5725-2 standard [1] and in second part the calculation of statistical indicator Z-score with ISO13528 [5] standard to assess of proficiency of laboratory with the first estimated parameters. However, these statistical methods rely on the assumption that the measurement... |
| Tipo: Text |
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| Ano: 2017 |
URL: https://archimer.ifremer.fr/doc/00693/80493/83680.pdf |
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