This paper describes the preliminary results of the design, development and characterization of precision artifacts for the measurement of low forces of 1 N and 2 N. For designing the elastic element, we carried out the finite element analysis (FE) to determine the stress and strain distribution on the elastic element for appropriately identifying the location for fixing the strain gauges. In order to obtain optimum performance and sensitivity, the strain gauges are emplaced on the identified location using a high quality curing adhesive. Characterization of these artifacts are performed on a recently developed low force dead weight machine having an estimated best measurement capability (BMC) of ± 0.0012% (k = 2). The repeatability and reproducibility of the developed artifact are found to be within ± 0.003% and ± 0.006% respectively.

Two linear fitting procedures are applied to internationally reference data in refractometry of solutions. Least square linear regression is compared to linear interpolation in the intervals of the two successive referenced data. The formulas and the validity of the procedures are shortly presented. The results are comparable, but for faster results, the linear regression method is preferred to the interpolation by intervals, albeit their bigger uncertainties values.

A swarm-intelligence solution to industrial problems of automatic multiple-faults diagnostics is proposed. In particular, drawbacks of swarm-based algorithms in heuristic search strategy related to the mutual dependence of solutions are overcome by a likelihood-based trail intensity modification of ant-colony optimization. Experimental results of comparison tests with an evolutionary state-of-the-art solution of a case study on an advanced industrial system for remote monitoring, diagnostics, and maintenance are reported.

The assessment of the geometry of artefacts in length metrology is concerned with estimating dimension, form and roughness. While all three are positive quantities, the evaluation of form and roughness are problematic, mainly because the values of the parameters to be measured are often of the same order as the measurement uncertainty. Furthermore, random effects associated with a measurement system will in general bias the estimate of parameter. This paper discusses these issues, using a Bayesian approach in which prior distributions are used to ensure parameter estimates are physically meaningful.

This paper describes the new primary low-range dew-point generator at LPM developed in cooperation with MIKES through EUROMET project no.912. The generator is designed for primary realisation of the dew-point temperature scale from -70 °C to +5 °C. The principle and the design of the generator are described in detail and schematically depicted. Results of the preliminary efficiency tests of it's saturator show that it is efficient enough for a primary realisation of the dew-point temperature scale. Standard uncertainties due to the non-ideal saturation efficiency are estimated to be 0.02 °C.