DYNA JOURNAL ENGINEERING

Key words:

Montecarlo, dimensional metrology, angle construction, influence magnitudes, uncertainty propagation, ISO GUM, gauge blocks, sine bar, non-linear functions, measurement uncertainty, industrial engineering, programming, metrology, random numbers.

Article type:

ARTICULO DE INVESTIGACION / RESEARCH ARTICLE

Section:

RESEARCH ARTICLES

The Monte Carlo method (MCM), applied to uncertainty calculation in metrology, is well-suited for nonlinear functions. It also provides more accurate solutions in certain complex linear models. Although MCM is extensively covered in the ISO Guide to the Expression of Uncertainty in Measurement (GUM) and in metrological guides from reference institutions in various countries, industrial engineering curricula typically only introduce concepts related to uncertainty propagation using the traditional analytical method. MCM requires programming to generate random numbers within the expected range for each variable involved in the metrological system, combining computing tools with metrology. This methodological proposal is based on a basic system for constructing an angle using a sine bar and gauge blocks. The problem progressively incorporates the temperature variable under different behavioural hypotheses and the influence of other factors, such as the roundness tolerance of the sine bar supports. The results obtained using MCM are compared with those from the classical GUM method, and the analysis demonstrates the robustness of MCM from a scientific perspective. Based on this methodology, further challenges could be explored, such as introducing the flatness tolerance of the surface plate used.

Keywords: Montecarlo, dimensional metrology, angle construction, influence magnitudes