Modeling the systematic behavior at the micro and nano length scale
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The brisk progression of the industrial digital innovation, leading to high degree of automation and big data transfer in manufacturing technologies, demands continuous development of appropriate off-line metrology methods to support processes' quality with a tolerable assessment of the measurement uncertainty. On the one hand specific-area references propose methods that are not yet well optimized to the changed background, and on the other, international general recommendations guide to effective uncertainty evaluation, but suggesting procedures that are not necessarily proven efficient at the micro- and nano-dimensional scale. The well-known GUM approach (i.e. frequentist statistics) was analyzed with the aim to test consistently its applicability to micro/nano dimensional and surface topography measurements. The investigation assessed three different clarifying situations, giving rise to consistent model equations, and to the achievement of the traceability. The choice of the cases provided a number of influence factors, which are typical liabilities at the micro and nano-length scale, and that have been related to the correction of the systematic behavior, viz. the amount of repeated measurements, the time sequence of the acquired micrographs and the instruments used. Such approach allowed the successful implementation of the GUM approach to micro/nano dimensional and topographic measurements, and also the appraisal of the level of efficacy of the method, its application limits and hints on possible future developments.
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