1.1本规程描述了为金属、矿石和相关材料的化学分析建立符合ISO 17025的不确定度预算的模型。它基于将霍维茨函数应用于广泛接受的、多样的实验室间测试程序，例如标准测试方法的实验室间测试和能力验证程序。该函数表示任何浓度水平的实验室间标准偏差，因为主管实验室使用优化的测试程序来分析任何分析物的任何基质。 它可用于设置aim不确定性，根据这些不确定性规划新的标准试验方法，并评估现有试验方法的性能。 1.2优化试验程序是指最终试验结果至少等同于替代最先进程序的程序。在分析化学界，这意味着进行、验证和控制校准，以使最终测试结果没有系统的、可检测的偏差。消除偏差源是任何设计分析测试方法的人的关键责任。 因此，包含系统、可测量偏差来源的分析测试方法可能不被接受为ASTM测试方法，其性能数据可能不符合本规程中描述的程序。 1.3本规程中描述的不确定度预算模型基于以下假设:在正态分布、无偏差的环境中，测量不确定度将提高2的平方根，每次去除一个重要的变化源。 相反，假设每次添加一个重要的变化源时，测量不确定度将恶化相同的程度。此外，该模型假设，任何基于成分的测量系统中增加变化的层次结构从校准开始，并通过控制实验室内标准差到实验室间标准差，再到合格评定的产品取样。因此，可以使用该模型预测任何过程步骤的预期不确定性的目标值。 1.4使用该模型时，使用该模型生成的目标值必须进行验证、验证和记录，作为任何新测试方法、采样实践和产品规范（视情况而定）的开发和实验室间测试的一部分。还预计，选择使用该标准试验方法的每个实验室将生成数据，以表明标准试验方法符合标准试验方法实验室间试验期间产生的公布不确定度。 本规程中的原则也可用于制定用于确定其他材料成分的试验方法。 1.5 本标准并非旨在解决与其使用相关的所有安全问题（如有）。本标准的用户有责任在使用前制定适当的安全和健康实践，并确定监管限制的适用性。

1.1 This practice describes a model for establishing ISO 17025-compliant uncertainty budgets for the chemical analysis of metals, ores, and related materials. It is based on applying the Horwitz function to widely accepted, diverse interlaboratory test programs, such as interlaboratory testing of standard test methods and proficiency testing programs. This function expresses the interlaboratory standard deviations that can be expected for any concentration level as competent laboratories use optimized test procedures to analyze any matrix for any analyte. It may be used to set aim uncertainties against which to plan new standard test methods and to assess the performance of existing test methods. 1.2 An optimized test procedure is one in which the final test results are at least equivalent to alternative, state-of-the-art procedures. In the analytical chemistry community, this means that calibrations are carried out, verified, and controlled such that the final test results have no systematic, detectable bias. The elimination of sources of bias is a key responsibility of any person who designs analytical test methods. Hence, an analytical test method that contains systematic, measurable sources of bias would probably not be accepted as an ASTM test method and its performance data would probably not be in compliance with the procedures described in this practice. 1.3 The uncertainty budget model described in this practice is based on the assumption that, in a normally distributed, bias-free environment, measurement uncertainty will improve by the square root of two with each removal of a significant source of variation. Conversely, it is assumed that measurement uncertainty will worsen by the same amount with each addition of a significant source of variation. Furthermore, this model assumes that the hierarchy of increasing variation in any composition-based measurement system begins with calibration and progresses through control to intralaboratory standard deviation to interlaboratory standard deviation to product sampling for conformity assessment. Therefore, aim values for the expected uncertainties at any process step can be predicted using this model. 1.4 When using this model, the aim values generated using this model must then be validated, verified, and documented as part of the development and interlaboratory testing of any new test method, sampling practice, and product specification, as appropriate. It is also expected that each laboratory that elects to use that standard test method will generate data to show that the standard test method complies with the published uncertainties developed during interlaboratory testing of the standard test method. The principles in this practice can also be applied to the development of test methods used to determine the composition of other materials. 1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.