A modified Monte Carlo method to study the performance of the roughness models Online publication date: Tue, 30-Jan-2018
by Y. Ech-Charqy; H. Gziri; M. Essahli
International Journal of Manufacturing Technology and Management (IJMTM), Vol. 32, No. 2, 2018
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.
Online publication date: Tue, 30-Jan-2018
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Manufacturing Technology and Management (IJMTM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com