Multi objective prediction and optimization of control parameters in the milling of aluminium hybrid metal matrix composites using ANN and Taguchi-grey relational analysis

作     者：S.Ajith Arul Daniel R.Pugazhenthi R.Kumar S.Vijayananth 

作者机构：Department of Mechanical Engineering Vels Institute of ScienceTechnology and Advanced Studies 

出 版 物：《Defence Technology（防务技术）》 (Defence Technology)

年 卷 期：2019年第15卷第4期

页      面：545-556页

核心收录：

学科分类：08[工学] 0826[工学-兵器科学与技术] 

主　　题：Silicon carbide Temperature Surface roughness Cutting forces Artificial neural network Grey relational analysis 

摘      要：This study aims to optimize the input parameters such as mass fraction and particle size of SiC along with depth of cut,feed and cutting speed in the milling of Al5059/SiC/*** hybrid metal matrix composites are generally fabricated by reinforcing of different sizes(10,20,40 μm)of SiC with aluminium at a different levels(5%,10%& 15%)whereas the MoS2 addition is fixed as 2%.The effect of each control factor on response variables are analyzed through Taguchi S/N ratio ***,the most significant method for prediction of response parameters is satisfied by ANN model than the regression *** of variance(ANOVA)results envisage that mass fraction of SiC,feed rate is the most domineering factor on response variable.