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Measurement uncertainty is an important component of modern materials analysis: it indicates the boundaries within which the test results can be trusted. Such results are necessary for understanding of, for example, material and product tolerances and lifetimes, vital for plastic product reliability and safety.
Determination of measurement uncertainty is normally quite laborious, but this book shows how the available interlaboratory test data for plastics can be used to calculate measurement uncertainty much more simply. It contains many interlaboratory test results in the fields of thermoanalysis, molar mass determination, and quantitative analysis of the composition of material, presented in tables and graphical charts, discussed in the text, and elaborated by practical examples.
In addition to the evaluation by means of the presented data (top-down approach), the relationship to the bottom-up approach specified in the Guide to the Expression of Uncertainty in Measurement (GUM) is explained based on an example. Further sections deal with sampling, and the issue of whether or not the difference between analytical results is significant.
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Measurement uncertainty is an important component of modern materials analysis: it indicates the boundaries within which the test results can be trusted. Such results are necessary for understanding of, for example, material and product tolerances and lifetimes, vital for plastic product reliability and safety.
Determination of measurement uncertainty is normally quite laborious, but this book shows how the available interlaboratory test data for plastics can be used to calculate measurement uncertainty much more simply. It contains many interlaboratory test results in the fields of thermoanalysis, molar mass determination, and quantitative analysis of the composition of material, presented in tables and graphical charts, discussed in the text, and elaborated by practical examples.
In addition to the evaluation by means of the presented data (top-down approach), the relationship to the bottom-up approach specified in the Guide to the Expression of Uncertainty in Measurement (GUM) is explained based on an example. Further sections deal with sampling, and the issue of whether or not the difference between analytical results is significant.