1.1 本实践涵盖了程序的设计和操作信息，该程序使用一系列公认的统计质量控制（SQC）程序和工具来监测和控制选定分析测量系统的持续稳定性、精密度和偏差性能。 附注1: 选择适用本惯例的测量系统和确定适用频率的完整标准列表超出了本惯例的范围。但是，需要考虑的一些因素包括（ 1 ）分析测量系统的使用频率，（ 2 ）被测参数的临界性，（ 3 ）基于历史数据的系统稳定性和精度性能，（ 4 ）商业经济学，以及（ 5 ）法规、合同或测试方法要求。1.2 本实践适用于在连续数值尺度上产生结果的稳定分析测量系统。 1.3 本规范适用于实验室试验方法。 1.4 本规范适用于经验证的工艺流分析仪。 1.5 本规范适用于监测两个旨在测量相同性质的分析测量系统之间的差异，前提是这两个系统都已根据实践中的统计方法进行了评估 D6708 以及应用的适当偏差。 附注2: 有关单变量工艺流程分析仪的验证，另请参见实践 D3764 . 附注3: 中的一个或两个分析系统 1.5 可以是实验室测试方法或经验证的工艺流分析仪。 1.6 该实践假设，当测量系统处于统计控制状态时，正常（高斯）模型足以描述和预测测量系统行为。附注4: 对于非高斯过程，测试结果的转换可以允许这些工具的适当应用。咨询统计学家以获得进一步的指导和信息。 1.7 本国际标准是根据世界贸易组织技术性贸易壁垒（TBT）委员会发布的《关于制定国际标准、指南和建议的原则的决定》中确立的国际公认的标准化原则制定的。 ======意义和用途====== 5.1 该实践可用于持续证明用于建立和确保石油和石油产品质量的分析测量系统的熟练程度。 5.2 使用本实践中包含的技术积累的数据提供了监控分析测量系统精度和偏差的能力。5.3 这些数据对于更新测试方法以及指示潜在测量系统改进的领域非常有用。 5.4 控制图统计可用于计算在现场精密度条件下获得的相同样品的两个单一结果之间的符号差异(Δ)预计落在约5%的时间之外的限度，其中每个结果是在同一实验室中使用不同的测量系统执行相同的测试方法，并且两个系统都处于统计控制状态。

1.1 This practice covers information for the design and operation of a program to monitor and control ongoing stability and precision and bias performance of selected analytical measurement systems using a collection of generally accepted statistical quality control (SQC) procedures and tools. Note 1: A complete list of criteria for selecting measurement systems to which this practice should be applied and for determining the frequency at which it should be applied is beyond the scope of this practice. However, some factors to be considered include ( 1 ) frequency of use of the analytical measurement system, ( 2 ) criticality of the parameter being measured, ( 3 ) system stability and precision performance based on historical data, ( 4 ) business economics, and ( 5 ) regulatory, contractual, or test method requirements. 1.2 This practice is applicable to stable analytical measurement systems that produce results on a continuous numerical scale. 1.3 This practice is applicable to laboratory test methods. 1.4 This practice is applicable to validated process stream analyzers. 1.5 This practice is applicable to monitoring the differences between two analytical measurement systems that purport to measure the same property provided that both systems have been assessed in accordance with the statistical methodology in Practice D6708 and the appropriate bias applied. Note 2: For validation of univariate process stream analyzers, see also Practice D3764 . Note 3: One or both of the analytical systems in 1.5 may be laboratory test methods or validated process stream analyzers. 1.6 This practice assumes that the normal (Gaussian) model is adequate for the description and prediction of measurement system behavior when it is in a state of statistical control. Note 4: For non-Gaussian processes, transformations of test results may permit proper application of these tools. Consult a statistician for further guidance and information. 1.7 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee. ====== Significance And Use ====== 5.1 This practice may be used to continuously demonstrate the proficiency of analytical measurement systems that are used for establishing and ensuring the quality of petroleum and petroleum products. 5.2 Data accrued, using the techniques included in this practice, provide the ability to monitor analytical measurement system precision and bias. 5.3 These data are useful for updating test methods as well as for indicating areas of potential measurement system improvement. 5.4 Control chart statistics can be used to compute limits that the signed difference (Δ) between two single results for the same sample obtained under site precision conditions is expected to fall outside of about 5 % of the time, when each result is obtained using a different measurement system in the same laboratory executing the same test method, and both systems are in a state of statistical control.