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IUPAC/CITAC Guide: Classification, modeling and quantification of human errors in a chemical analytical laboratory (IUPAC Technical Report)

机译:IUPAC / CITAC指南:化学分析实验室中人为错误的分类,建模和定量(IUPAC技术报告)

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摘要

The classification, modeling, and quantification of human errors in routine chemical analysis are described. Classifications include commission errors (mistakes and violations) and omission errors (lapses and slips) in different scenarios at different steps of the chemical analysis. A Swiss cheese model is used to characterize error interaction with a laboratory quality system. The quantification of human errors in chemical analysis, based on expert judgments, i.e. on the expert(s) knowledge and experience, is applied. A Monte Carlo simulation of the expert judgments was used to determine the distributions of the error quantification scores (scores of likelihood and severity, and scores of effectiveness of a laboratory quality system against the errors). Residual risk of human error after the error reduction by the laboratory quality system and consequences of this risk for quality and measurement uncertainty of chemical analytical results are discussed. Examples are provided using expert judgments on human errors in pH measurement of groundwater, multi-residue analysis of pesticides in fruits and vegetables, and elemental analysis of geological samples by inductively coupled plasma mass spectrometry.
机译:描述了常规化学分析中人为错误的分类,建模和量化。分类包括在化学分析的不同步骤的不同情况下的佣金错误(错误和违规)和遗漏错误(失效和漏失)。瑞士奶酪模型用于表征与实验室质量体系的错误交互。基于专家的判断,即基于专家的知识和经验,对化学分析中的人为错误进行量化。专家判断的蒙特卡罗模拟被用来确定误差量化分数的分布(可能性和严重性分数,以及实验室质量体系针对误差的有效性分数)。讨论了通过实验室质量体系减少错误后的人为错误残余风险以及这种风险对质量和化学分析结果不确定性的后果。通过对地下水pH值测量中人为错误的专家判断,水果和蔬菜中农药的多残留分析以及通过电感耦合等离子体质谱法对地质样品进行元素分析的专家判断,提供了示例。

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