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2. Measurement Process Characterization
2.1. Characterization
2.1.1. What are the issues for characterization?

Bias and Accuracy

Definition of Accuracy and Bias Accuracy is a qualitative term referring to whether there is agreement between a measurement made on an object and its true (target or reference) value. Bias is a quantitative term describing the difference between the average of measurements made on the same object and its true value. In particular, for a measurement laboratory, bias is the difference (generally unknown) between a laboratory's average value (over time) for a test item and the average that would be achieved by the reference laboratory if it undertook the same measurements on the same test item.
Depiction of bias and unbiased measurements
depiction of unbiased measurements Unbiased measurements relative to the target

depiction of biased measurements Biased measurements relative to the target
Identification of bias Bias in a measurement process can be identified by:
  1. Calibration of standards and/or instruments by a reference laboratory, where a value is assigned to the client's standard based on comparisons with the reference laboratory's standards.
  2. Check standards , where violations of the control limits on a control chart for the check standard suggest that re-calibration of standards or instruments is needed.
  3. Measurement assurance programs, where artifacts from a reference laboratory or other qualified agency are sent to a client and measured in the client's environment as a 'blind' sample.
  4. Interlaboratory comparisons, where reference standards or materials are circulated among several laboratories.
Reduction of bias Bias can be eliminated or reduced by calibration of standards and/or instruments. Because of costs and time constraints, the majority of calibrations are performed by secondary or tertiary laboratories and are related to the reference base via a chain of intercomparisons that start at the reference laboratory.

Bias can also be reduced by corrections to in-house measurements based on comparisons with artifacts or instruments circulated for that purpose (reference materials).

Caution Errors that contribute to bias can be present even where all equipment and standards are properly calibrated and under control. Temperature probably has the most potential for introducing this type of bias into the measurements. For example, a constant heat source will introduce serious errors in dimensional measurements of metal objects. Temperature affects chemical and electrical measurements as well.

Generally speaking, errors of this type can be identified only by those who are thoroughly familiar with the measurement technology. The reader is advised to consult the technical literature and experts in the field for guidance.

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