A modified Monte Carlo method to study the performance of the roughness models

Y. Ech-Charqy, H. Gziri and M. Essahli

International Journal of Manufacturing Technology and Management, 2018, vol. 32, issue 2, 176-188

Abstract: Several empirical and mathematical models have been proposed to predict the surface roughness, but they are more or less effective in determining an approximate value to the real one, especially when we worked in a specific constraint that can cause errors in results. Hence, it is necessary to use an efficient method to determinate the more performance model, and to minimise the error range. In this work, we will propose a method modified of Monte Carlo algorithm (MMC) with an output Boolean signal and a performance ratio (PR) to study the performance of surface roughness models under specified constraints. It is a powerful and simple strategy based on Monte Carlo algorithm, which determine the possibility of finding the desired roughness values in a specified range, choosing the most efficient model to minimise inadequate results to our predicting values.

Keywords: methodology; model performance; modified Monte Carlo; MMC; performance algorithm; roughness; super-finishing. (search for similar items in EconPapers)
Date: 2018
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