In the present work, all steps involved in the measurement of Brinell hardness indentations were studied, with the main purpose of evaluating the contribution of each step to the total uncertainty of the process. For the measurement of the indentations an expert system using digital image processing was developed. This automatic procedure can be very helpful as it reduces by orders of magnitude the time needed to perform the measurements and makes the process more reproducible by reducing the influence of the human operator.

Precision design work and tight manufacturing tolerances demand highly accurate measurements. A Vector Network Analyzer (VNA) is one of the most important aids for linear RF analog designs. It can give accurate information about the passive network performance in both the frequency domain and the time domain. Designers heavily rely on these measurement results to locate the design problems and to evaluate the network performance. But the measurement errors always exist. In any high frequency measurement, there are measurement errors associated with the system that contribute uncertainty to the results. Therefore, measurement accuracy of a VNA is an important concern to the instrument designers and suppliers. This paper gives the overview of the uncertainty and errors associated with VNA measurement. Based on the low cost Vector Network Analyzer developed by INTEC, University of Gent, Belgium, the estimations of the uncertainty and errors in the reflection and transmission measurements are discussed. The measurement results are present to illustrate the improvement of the measurement accuracy after taking into account these measurement issues in the design procedure.

Measured data of blood chemical analysis have dispersion results in themselves, but if a statistical analysis is applied to the results, an effective factor is obtained on accuracy quality control. As a method, there is the one which confirms the existence of abnormal reaction products by Michalies-Menten factor. This factor expresses the relation between the change of concentration of reagent and measurement data, and also the factor discriminates the good or bad of blood test reagent. And in this study, the effect of deposit days of the factor was studied. Then in this study, the reagent of Radioimmunoassay (RIA) was selected as an experiment object. The RIA is a kind of blood chemical analysis.
In this paper, the accuracy of calibration curve of RIA was studied, and the good or bad of calibration curve was discriminated by using Michaelies-Menten factor. And then the discussion of time series variation data that the calibrator reagent changes in a deposit day was done.

The results of optimization of a measuring system applied to the identification of a human respiratory tract by a method of forcing non-periodic pressure changes are presented in the paper. The aim of the optimization is minimizing errors of determination of the parameters of a model describing a system being identified in the multidimensional technological space of the applied measuring tools and the parameters of the measurement experiment and identification algorithm. The results obtained in the simulation process showed that the optimum properties of the identification system can be obtained without using the equipment with extreme parameters, i.e. the expensive equipment. This result is contradictory to the approach commonly employed to the design of measuring systems applied in the parametric identification.

The ISO-GUM (Guide for Uncertainty Measurement) is a milestone in the history of uncertainty analysis, but practical procedures have still not been completely defined. In order to clarify some operative aspects, this paper proposes a practical improvement to the GUM, presenting a step-by-step procedure that illustrates how to evaluate uncertainty, developing analysis in parallel with the measurement process of the parameter. Following the ISO-GUM baseline, the proposed procedure is subdivided into: a) modelling stage: before designing a measurement chain suitable for a certain parameter, the modelling of the physical system under analysis and of the measurement system used to acquire that parameter is examined; b) instrument design stage: the metrological characteristics of each component of the measurement chain are analysed, also considering the traceability of reference samples; c) advanced stage: all previously detected components are combined with those from test operating conditions, e.g., effects of time, interfering and modifying disturbances; d) correction stage: the systematic effects are accounted for; e) indirect measurement stage: uncertainty propagated to the result of an indirect measurement is obtained by means of sensitivity indexes.