{"title":"The role of uncertainty of measurement In conformance testing","authors":"S. Sidney","doi":"10.51843/wsproceedings.2014.38","DOIUrl":null,"url":null,"abstract":"The vast majority of routine testing that takes place requires that the laboratory or the customer of the laboratory evaluates the test results in terms of either prescribed (regulations) or production limits. In more recent times simple acceptance rules that have been established over time have given way to a more ´scientific’ approach. These new ideas are intended to provide users of test and calibration reports that are specifically used for Conformance Testing, with more comprehensive support when the data is questionable. This paper reflects on what is questionable data, how it arises and makes reference to a new guidance document that was developed by the BIPM Joint Working Group on Guides • WG1 and published in 2012. It tackles the thorny question of Uncertainty of Measurement in Conformance Testing and provides a number of approaches which can be taken to help resolve issues that may arise. Although the BIPM, and this working group in particular, have traditionally focused on metrological issues, this approach will be of interest to all laboratories. As the role of uncertainty of measurement impacts more and more on certificates being issued, laboratories need to not only be aware of the effect that this has on conformance testing, but also be knowledgeable about how to answer customer’s queries in this regard. It is also hoped that authorities and regulators will start to adopt some of these ideas in order to avoid the cost or risk of incorrect decisions and it is hoped that this will also have a positive effect on decisions made as a result of laboratory data.","PeriodicalId":446344,"journal":{"name":"NCSL International Workshop & Symposium Conference Proceedings 2014","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NCSL International Workshop & Symposium Conference Proceedings 2014","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.51843/wsproceedings.2014.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The vast majority of routine testing that takes place requires that the laboratory or the customer of the laboratory evaluates the test results in terms of either prescribed (regulations) or production limits. In more recent times simple acceptance rules that have been established over time have given way to a more ´scientific’ approach. These new ideas are intended to provide users of test and calibration reports that are specifically used for Conformance Testing, with more comprehensive support when the data is questionable. This paper reflects on what is questionable data, how it arises and makes reference to a new guidance document that was developed by the BIPM Joint Working Group on Guides • WG1 and published in 2012. It tackles the thorny question of Uncertainty of Measurement in Conformance Testing and provides a number of approaches which can be taken to help resolve issues that may arise. Although the BIPM, and this working group in particular, have traditionally focused on metrological issues, this approach will be of interest to all laboratories. As the role of uncertainty of measurement impacts more and more on certificates being issued, laboratories need to not only be aware of the effect that this has on conformance testing, but also be knowledgeable about how to answer customer’s queries in this regard. It is also hoped that authorities and regulators will start to adopt some of these ideas in order to avoid the cost or risk of incorrect decisions and it is hoped that this will also have a positive effect on decisions made as a result of laboratory data.