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Human being as a part of measuring system influencing measurement results

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  • In memory of Paul De Bièvre
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Abstract

The role of human being as a part of a measuring system in a chemical analytical laboratory is discussed. It is argued that a measuring system in chemical analysis includes not only measuring instruments and other devices, reagents and supplies, but also a sampling inspector and/or analyst performing a number of important operations. Without this human contribution, a measurement cannot be carried out. Human errors, therefore, influence the measurement result, i.e., the measurand estimate and the associated uncertainty. Consequently, chemical analytical and metrological communities should devote more attention to the topic of human errors, in particular at the design and development of a chemical analytical/test method and measurement procedure. Also, mapping human errors ought to be included in the program of validation of the measurement procedure (method). Teaching specialists in analytical chemistry and students how to reduce human errors in a chemical analytical laboratory and how to take into account the error residual risk, is important. Human errors and their metrological implications are suggested for consideration in future editions of the relevant documents, such as the International Vocabulary of Metrology (VIM) and the Guide to the Expression of Uncertainty in Measurement (GUM).

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Correspondence to Ilya Kuselman.

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The author Walter Bich is Convener of the Joint Committee for Guides in Metrology (JCGM) Working Group 1 (Guide to the Expression of Uncertainty in Measurement—GUM). The opinion expressed in this paper does not necessarily represent the view of this Working Group.

Papers published in this section do not necessarily reflect the opinion of the Editors, the Editorial Board and the Publisher.

A critical and constructive debate in the Discussion Forum or a Letter to the Editor is strongly encouraged!

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Kuselman, I., Pennecchi, F., Bich, W. et al. Human being as a part of measuring system influencing measurement results. Accred Qual Assur 21, 421–424 (2016). https://doi.org/10.1007/s00769-016-1239-3

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  • DOI: https://doi.org/10.1007/s00769-016-1239-3

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