To reasonably improve the reliability of batch product inspection results and reduce the influence of measurement uncertainty on product qualification, the problem of product misjudgment rate in total inspection was studied, and the quantitative formula of product quality misjudgment risk was deduced. Two kinds of errors in product inspection and the conditions for producing errors are analyzed, and the calculation formula of misjudgment rate for different errors is studied. The example results show that the proposed quantitative model can comprehensively reflect the risk of misjudgment in product inspection caused by measurement uncertainty, and the quantitative data can more directly reflect the risk of both producer and consumer sides, thus prompting the inspectors to judge the qualifications more carefully.
There are a large amount of input quantities and complicated correlation of uncertainty source which limit the reliability of the GUM method to evaluate the uncertainty of the measurement result in the fan energy efficiency test system. Based on the technical advantages of computer random sampling, Monte Carlo uncertainty evaluation method was given to solve the correlation of uncertainty sources of fan energy efficiency test system in traditional GUM method. It can be concluded through the experiment that the results of the GUM method without considering the correlation were basically consistent with the results of the MCM method obtained by computer sampling.