Prediction of Cutting Forces with Neural Network by Milling Functionally Graded Material

被引:10
作者
Irgolic, Tomaz [1 ]
Cus, Franc [1 ]
Paulic, Matej [1 ]
Balic, Joze [1 ]
机构
[1] Univ Maribor, Fac Mech Engn, SLO-2000 Maribor, Slovenia
来源
24TH DAAAM INTERNATIONAL SYMPOSIUM ON INTELLIGENT MANUFACTURING AND AUTOMATION, 2013 | 2014年 / 69卷
关键词
LENS; functionally graded material; cutting parameters; artificial neural network; MECHANICAL-PROPERTIES; PARAMETERS; STEELS;
D O I
10.1016/j.proeng.2014.03.057
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Paper shows the general characteristics of graded materials, their previous industrial use and potential use of graded materials in the future. In any case, today the use of graded materials is increasing and moving from the laboratory environment into everyday use. However, the subsequent processing of the graded material remains the big unknown, and represents a major challenge for researchers and industry around the world. It could be said that the study of machinability of these materials is in its infancy and in this area are many unanswered questions. Machinability problem of graded materials was undertaken at the Faculty of Mechanical Engineering in Maribor. After a radical study of the literature and potential machining processes of graded materials, we started with the implementation of cutting processes on the workpiece. This professional paper presents the first results of the analysis, which will be used for further research and machinability study of graded materials. Also prediction of cutting forces with neural network by milling functionally graded material was made. In paper first predicted cutting forces by milling graded material are presented. (C) 2014 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:804 / 813
页数:10
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