Int. J. Metrol. Qual. Eng.
Volume 8, 2017
|Number of page(s)||9|
|Published online||24 May 2017|
Comparison of GUM and Monte Carlo methods for the uncertainty estimation in hardness measurements
National Institute of Standards,
Tersa St, El-Haram, Box 136 Code 12211,
⁎ Corresponding author: email@example.com
Accepted: 2 May 2017
Monte Carlo Simulation (MCS) and Expression of Uncertainty in Measurement (GUM) are the most common approaches for uncertainty estimation. In this work MCS and GUM were used to estimate the uncertainty of hardness measurements. It was observed that the resultant uncertainties obtained with the GUM and MCS without correlated inputs for Brinell hardness (HB) were ±0.69 HB, ±0.67 HB and for Vickers hardness (HV) were ±6.7 HV, ±6.5 HV, respectively. The estimated uncertainties with correlated inputs by GUM and MCS were ±0.6 HB, ±0.59 HB and ±6 HV, ±5.8 HV, respectively. GUM overestimate a little bit the MCS estimated uncertainty. This difference is due to the approximation used by the GUM in estimating the uncertainty of the calibration curve obtained by least squares regression. Also the correlations between inputs have significant effects on the estimated uncertainties. Thus the correlation between inputs decreases the contribution of these inputs in the budget uncertainty and hence decreases the resultant uncertainty by about 10%. It was observed that MCS has features to avoid the limitations of GUM. The result analysis showed that MCS has advantages over the traditional method (GUM) in the uncertainty estimation, especially that of complex systems of measurement. MCS is relatively simple to be implemented.
Key words: uncertainty / normal distribution / Monte Carlo / guideline for uncertainty of measurement / correlation
© G.M. Mahmoud and R.S. Hegazy, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.