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METROLOGICAL COMPETENCE OF LENGTH MEASUREMENTS IN A PRIMARY LEVEL CALIBRATION FACILITY

机译:主要校准设施中长度测量的计量能力

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Metrological competence is the ability to perform comparative measurements and to disseminate the measurement information over some specified range and within acceptable limits of uncertainty for a designated physical quantity. The acceptable limits of measurement uncertainty have been defined as: (1) The bias of the measurements at the laboratory should be no greater than three times the systematic error at a typical national laboratory, and (2) the precision error of the laboratory measurements should be no greater than ten times those suffered for the same measurements at a typical national laboratory. The paper specifically discusses achievement of metrological competence of length measurements at the Measurement Standards Laboratory (MSL) of KFUPM Research Institute which is Saudi Arabia's first world-class calibration laboratory of primary level. The approach to prove the metrological competence is that an on-going measurement assurance program for gage blocks checks for the precision error of the process and occasional blind tests on national laboratory-calibrated gage blocks ascertain the laboratory bias. It is emphasized that one-time proof of competency is of little value; the evidence should be on a continuing basis. That is, the equipment, the operator, the procedure and the environment—all should play their role in characterizing the measurement process or determining the metrological competence. Measurement is thus a process not an isolated event. Any measurement at hand should be a random draw from a stable probability distribution; only then statements can be made about the health of the process.
机译:计量能力是执行比较测量的能力,并在某些指定范围内传播测量信息,以及指定物理量的可接受的不确定性范围内。可接受的测量不确定性限制已被定义为:(1)实验室的测量的偏差应不超过典型国家实验室系统错误的三倍,(2)实验室测量的精确误差应该在典型的国家实验室在典型的国家实验室遭受相同测量的十倍。本文具体探讨了KFUPM研究所的测量标准实验室(MSL)的长度测量的计量能力的成就,该研究所是沙特阿拉伯的初级世界级校准实验室。证明了计量能力的方法是,对于数量的测量保证规划,用于检查过程的精确误差和国家实验室校准的量大块的盲目测试确定了实验室偏见。强调,一次性能力证明程度较少;证据应该是继续持续的。也就是说,设备,操作员,程序和环境 - 所有人都应该在表征测量过程或确定计量能力时起作用。因此,测量不是一个孤立的事件的过程。手头的任何测量应该是从稳定的概率分布中抽取;只有那么陈述可以对过程的健康状况。

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