1.1 本指南描述了一种协议，用于优化、控制和报告同一实验室组织中多个工作站的测试方法不确定性。当不同的测试方法、不同的仪器或同一实验室组织的不同部分独立运行以验证或验证特定分析测量的准确性时，本标准不适用。 1.2 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。 ====意义和用途====== 4.1 许多有能力的分析实验室符合公认的质量体系要求。 使用标准试验方法时，其在相同样品上的试验结果应与标准中公布的再现性估计指数（R）内的其他类似实验室的结果一致。再现性估计是作为实践中所述类型的实验室间研究（ILS）的一部分生成的 E1601 . 合格实验室参与能力测试，如按照惯例进行的能力测试 E2027年 ，以确认他们随着时间的推移表现一致。在ILS和能力验证协议中，通常假设只有一个工作站用于生成数据。 4.2 许多实验室有工作量或后勤要求，或两者都有，这决定了多个工作站的使用。有些在同一地区有多个工作站（中央实验室格式）。 其他站点分散在整个设施中（以线路实验室形式），在某些情况下甚至可能位于不同的设施中。通常，分析报告不会识别用于测试的工作站，即使工作站的测试不确定性不同。如果客户端错误地将报告值的变化归因于进程，而不是工作站的变化，则可能会出现问题。如果实验室组织确定与多个工作站报告的结果相关的总体不确定性，并评估分析不确定性对生产过程的重要性，则可以将这些问题降至最低。 4.3 本指南描述了一种协议，用于有效优化和控制用于执行相同测试的不同工作站的测试结果的可变性。 它协调校准和控制协议，从而为所有工作站提供相同级别的测量跟踪和控制。它简化了文件和培训要求，从而促进了人员分配的灵活性。最后，它提供了一个机会，可以声称能力测试测量可追溯到所有包含的工作站，无论在哪个工作站上测试了能力测试样本。使用该协议的潜在好处随着实验室组织中包含的工作站数量的增加而增加。 4.4 本指南可用于识别和量化与性能不佳的工作站相关的纠正措施带来的益处。它还提供了在改进后跟踪改进性能的方法。 4.5 假设所有使用本指南的人都将建立实验室质量体系。该系统应包括使用文件化程序，应用测量过程的统计控制，以及参与能力验证。ISO/IEC 17025描述了建立此类实验室质量体系的优秀模型。 4.6 该协议的一般原则可适用于其他类型的测量，如机械测试和在线过程控制测量，如温度和厚度测量。在这些领域，用户可能需要建立自己的模型来定义数据质量目标，而能力验证可能不可用或不适用。 4.7 特别重要的是，本指南的用户应负责确保根据本协议操作的工作站所做测量的准确性。 除上述检查外 6.2.3 ，鼓励实验室使用其他技术，包括但不限于在同一实验室内或与其他同等能力的实验室合作，通过独立方法分析某些材料。从仔细同步但未正确校准的多个工作站生成大量数据的风险显而易见，必须避免。 4.8 本指南无意为制定测量不确定度声明（如ISO/IEC 17025要求的不确定度声明）提供具体指导。然而，使用本指南生成的统计计算可能会提供用于计算扩展不确定度的一种a类不确定度分量的有用估计。 4.9 本指南不提供任何确定实验室组织中使用多个工作站相关偏差的指南。

1.1 This guide describes a protocol for optimizing, controlling, and reporting test method uncertainties from multiple workstations in the same laboratory organization. It does not apply when different test methods, dissimilar instruments, or different parts of the same laboratory organization function independently to validate or verify the accuracy of a specific analytical measurement. 1.2 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. ====== Significance And Use ====== 4.1 Many competent analytical laboratories comply with accepted quality system requirements. When using standard test methods, their test results on the same sample should agree with those from other similar laboratories within the reproducibility estimates index (R) published in the standard. Reproducibility estimates are generated as part of the interlaboratory studies (ILS), of the type described in Practice E1601 . Competent laboratories participate in proficiency tests, such as those conducted in accordance with Practice E2027 , to confirm that they perform consistently over time. In both ILS and proficiency testing protocols, it is generally assumed that only one work station is used to generate the data. 4.2 Many laboratories have workloads, or logistical requirements, or both, that dictate the use of multiple work stations. Some have multiple stations in the same area (central laboratory format). Other stations are scattered throughout a facility (at-line laboratory format) and in some cases may even reside at different facilities. Often, analysis reports do not identify the workstation used for the testing, even if workstations differ in their testing uncertainties. Problems can arise if clients mistakenly attribute variation in report values to process rather than workstation variability. These problems can be minimized if the laboratory organization determines the overall uncertainty associated with results reported from multiple workstations and assesses the significance of the analytical uncertainty to the production process. 4.3 This guide describes a protocol for efficiently optimizing and controlling variability in test results from different workstations used to perform the same test. It harmonizes calibration and control protocols, thereby providing the same level of measurement traceability and control to all workstations. It streamlines documentation and training requirements, thereby facilitating flexibility in personnel assignments. Finally, it offers an opportunity to claim traceability of proficiency test measurements to all included workstations, regardless on which workstation the proficiency test sample was tested. The potential benefits of utilizing this protocol increase with the number of workstations included in the laboratory organization. 4.4 This guide can be used to identify and quantify benefits derived from corrective actions relating to under-performing workstations. It also provides means to track improved performance after improvements have been made. 4.5 It is assumed that all who use this guide will have an established laboratory quality system. This system shall include the use of documented procedures, the application of statistical control of measurement processes, and participation in proficiency testing. ISO/IEC 17025 describes an excellent model for establishing this type of laboratory quality system. 4.6 The general principles of this protocol can be adapted to other types of measurements, such as mechanical testing and on-line process control measurements, such as temperature and thickness gauging. In these areas, users may need to establish their own models for defining data quality objectives and proficiency testing may not be available or applicable. 4.7 It is especially important that users of this guide take responsibility for ensuring the accuracy of the measurements made by the workstations to be operated under this protocol. In addition to the checks mentioned in 6.2.3 , laboratories are encouraged to use other techniques, including, but not limited to, analyzing some materials by independent methods, either within the same laboratory or in collaboration with other equally competent laboratories. The risks associated with generating large volumes of data from carefully synchronized, but incorrectly calibrated multiple workstations are obvious and must be avoided. 4.8 This guide is not intended to provide specific guidance on development of statements of measurement uncertainty such as those required by ISO/IEC 17025. However, the statistical calculations generated using this guide may provide a useful estimate of one Type A uncertainty component used in the calculation of an expanded uncertainty. 4.9 This guide does not provide any guidance for determining the bias related to the use of multiple workstations in a laboratory organization.