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Paper Details

Paper Title
Multi-Objective Optimization in CNC End Milling using Taguchi Optimization Technique
Abstract
The present work makes an attempt to analyzevarious parameters of end milling in order to minimize the surface roughness and to maximize the material removal rate (MRR) of Al 2024-SiC composite. Al2024-SiC is generally used in manufacturing high strength parts of aircrafts and machinery, fuselage structural wing tension members, wing skins, engine parts subjected to high temperaturesincluding gears and bolts and for security vans where strength is critical. The quality of the machined surface, i.e., surface finish and texture affects the function, appearance and reliability of a product. On the other hand higher production rate is possible when MRR is maximum. But higher MRR leads to lower surface finish, so a tradeoff between Surface finish and MRR is needed. In this work, the optimal selection of process parameters have been done in order to obtain optimized response output parameters namely surface roughness and MRR by using Taguchis technique. And ANOVA analysis. In machining operations, achieving desired surface quality is a bit difficult as these quality structures are influenced by the effect of process parameters and their interactions. However, the amounts of influence of the process parameters vary for different processes. Therefore, optimization of surface roughness and MRR is a multi-factor and multi-objective optimization which is carried out successfully by the help of Taguchi optimization technique.
Keyword
Surface Roughness, Material Removal Rate, Orthogonal Array, Taguchi Technique
Others Details
Paper Id : 65805
Author Name : Atul Kumar
Co-Author Name(s) : Dr. Sudhir KumarDr. Rohit Garg Dr. Neeraj Kumar
Volume/Issue No : Volume 04 Issue 07
Page No : 187-196
DOI Number : DOI:10.21090/IJAERD.65805
License : This work is licensed under a Creative Commons Attribution 4.0 International License.
website : http://www.ijaerd.com/index.php
Impact Factor : 5.71, SJIF-2017
ISSN Details : eISSN: 2348-4470, pISSN:2348-6406