Open AccessSmart prediction of surface micro-hardness after milling based on fuzzy inference model
Author(s) -
M. T. Amira,
Abderrahim Belloufi,
Mourad Abdelkrim,
Farid ABDELKRIM,
Mourad Mezoudj
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1018/1/012017
Subject(s) - machining , materials science , fuzzy inference , end milling , fuzzy logic , process (computing) , hardness , mechanical engineering , cnc milling , surface (topology) , metallurgy , process engineering , computer science , fuzzy control system , adaptive neuro fuzzy inference system , mathematics , engineering , artificial intelligence , numerical control , geometry , operating system
The lack of comprehending and control of the micro-hardness of the machined surface is an important obstacle to the use of the milling process. In order to optimize the machining process by milling, this work has focused on the problem of micro-hardness changing of machined surfaces by milling, which has been the subject of several scientific works. A fuzzy inference model was developed to study the influence of cutting conditions (cutting speed, feed per tooth and depth of cut) on the micro-hardness of machined surfaces by milling. The predicted values, obtained by fuzzy model, are compatible with the experimental values, with an average error percentage of 0.63%.