In this paper we introduce an approach for constructing statistical metrology tools with a Microsoft Excel based interface that uses the open source statistical package R as the computational engine. These metrology tools will enable Excel users to access a larger array of specialized statistical tools for metrology. We will describe our general approach and demonstrate one tool - an automated uncertainty calculator. This uncertainty calculator provides users with a simple and flexible tool for estimating measurement uncertainty using the methods outlined in the ISO Guide to the Expression of Uncertainty in Measurement, popularly known as the ISO GUM. The uncertainty calculator is easy to use for scientists who are comfortable with spreadsheets, can handle a variety of typical correlation structures, and performs a validity check on the results by simulating the coverage probabilities actually attained by the uncertainty intervals.

The paper deals with the problem of pointing out and mark the various kind of defects (mainly scars, wrinkles and fire brandings) of tanned calf leathers used in many industrial areas (e.g. household couches and car seats lining ones). In the first experiments here presented the authors try to use the same inspection method previously successfully applied to quality control of hands-made satin glasses, that is a two-dimensional wavelet-based de-noising technique of high resolution images of the leather under inspection; according to multiresolution analysis, this method produces a suitable number of decomposition levels of the image, then it carries out a thresholding operation on details and finally, using the threshold levels estimated considering the actual noise level, it assesses and mark the various kind of defects. The final aim of the work is the realization of an automatic and in-line computer vision system for leather analysis capable to accurately inspect and mark the defective areas of the analyzed leather specimens before they enter the production chain.

In the field of metrology it is common practice to approximate the results of a measurement by functions modelling physical facts. The most simple form of such an approximation is the linear fit. This article presents five different methods of linear fit in R² by working out the characteristic features of these methods like scale unit invariance. The author's intention is to be helpful in finding the most useful method from case to case.

Applications of modern, computer (software) controlled measuring systems are various, from automation of testing and calibration laboratories to legal metrology measuring instruments and systems. Requirements to be met by such instruments or systems are usually defined by national or international legislation or international technical, safety, or laboratory competence standards. Validation of fulfilment of these requirements is essential for the conformity assessment of these instruments and systems. The complexity of validation and resources needed in the validation process depend on the construction of the object of validation and may be very extensive, especially in the case of computer based measuring systems. Suggested approach for modular validation of complex measuring systems may reduce the validation efforts, as well as costs and time consumption.

The paper is on the usefulness of global optimization for developing variational algorithms of spectrophotometer calibration. A new nonlinear method for reconstruction of absorption spectrum, on the basis of spectrophotometric data, is proposed and used for demonstrating that the quality of reconstruction depends on the ability of the calibration procedure to reach a global minimum during optimization of the parameters of the operator of reconstruction. The results obtained using calibration algorithms based on local and global optimization are compared in terms of measurement uncertainty and artefact content.