Optimised Measurement Uncertainty and Decision-Making in Conformity Assessment

Abstract: Risks of incorrect decision-making in conformity assessment associated both with sampling and measurement uncertainties and rules which limit these risks are tackled with an economic decision theory approach. Earlier used in analytical measurement, this approach is extended to more generality where the costs of testing are balanced against the costs associated with the consequences of incorrect decision-making. A novel discussion of different models of consequence costs is included, covering measures of customer dissatisfaction. Examples cover the metering of energy, fuel and environmental emissions but also other commodities; all areas of increasing societal importance where costs are raising at the same time as more stringent accuracy requirements are successively introduced. A discussion in economic terms of common rules in conformity assessment is given, including the setting of limits on the maximum permissible uncertainty and measurement capability, as well as acceptance quality limits (AQL) and limiting quality limits (LQL) in attribute sampling. This economic approach is a complement to traditional sampling plans and treatment of risks in decision-making.

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