Neural network modeling for face milling operation

被引：0
|
作者：
Sureshkumar B. [1 ]
Vijayan V. [1 ]
Dinesh S. [1 ]
Rajaguru K. [1 ]
机构：
[1] Dept. of Mech. Engg., K. Ramakrishnan College of Tech, Samayapuram, Tamil Nadu
来源：
International Journal of Vehicle Structures and Systems | 2019年 / 11卷 / 02期
关键词：
Cutting force; Feed force; Neural network; Surface roughness; Temperature; Thrust force;
D O I：
10.4273/ijvss.11.2.20
中图分类号：
学科分类号：
摘要：
Milling operation is one of the important manufacturing processes in production industry. Study and analysis of milling process parameters such as spindle speed, feed rate and depth of cut are important for process planning engineers. The responses are temperature, surface roughness, machining time, feed force, thrust force and cutting force. The main aim of this study is to find out the effects of these parameters in face milling operation on Monel k 400 work piece materials with tungsten carbide insert. The theoretical investigation is carried out with neural network modelling and the 3-1-6 structure neural network models are considered. Developed neural network models show best agreement with experimental values. For same type of operation, result of these experiments shall be useful for future research purpose. © 2019. MechAero Foundation for Technical Research & Education Excellence.
引用
收藏
页码：214 / 219
页数：5
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