Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Multi-objective optimization in end milling of GFRP composites using Taguchi techniques with principal component analysis

Multi-objective optimization in end milling of GFRP composites using Taguchi techniques with... PurposeThe purpose of this paper is to find out the optimum machining parameters using Taguchi technique with principal component analysis (PCA) during end milling of GFRP composites.Design/methodology/approachIn multi-objective optimization, weight criteria of each objective are important for producing better and accurate solutions. This method has been employed for simultaneous minimization of surface roughness, cutting force and delamination factor. Experiments were planned using Taguchi’s orthogonal array with the machining parameters, namely, helix angle of the end mill cutter, spindle speed, feed rate and depth of cut were optimized with considerations of multiple response characteristics, including machining force, surface roughness and delamination as the responses. PCA is adopted to find the weight factors involved for all objectives. Finally analysis of variance concept is employed on multi-SN ratio to find out the relative significance of machining parameter in terms of their percentage contribution.FindingsThe multi-SN ratio is achieved by the product of weight factor and SN ratio to the performance characteristics in the utility concept. The results show that a combination of machining parameters for the optimized results has helix angle of 35°, machining speed of 4,000 m/min, feed rate of 750 mm/rev and depth of cut of 2.0 mm.Originality/valueEffect of milling of GFRP composites on delamination factor, surface roughness and machining force with various helix angle solid carbide end mill has not been analysed yet using PCA techniques. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Multidiscipline Modeling in Materials and Structures Emerald Publishing

Multi-objective optimization in end milling of GFRP composites using Taguchi techniques with principal component analysis

Download PDF
13 pages

Loading next page...
 
/lp/emerald-publishing/multi-objective-optimization-in-end-milling-of-gfrp-composites-using-Wxi8rb000h

References (31)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1573-6105
DOI
10.1108/MMMS-02-2016-0007
Publisher site
See Article on Publisher Site

Abstract

PurposeThe purpose of this paper is to find out the optimum machining parameters using Taguchi technique with principal component analysis (PCA) during end milling of GFRP composites.Design/methodology/approachIn multi-objective optimization, weight criteria of each objective are important for producing better and accurate solutions. This method has been employed for simultaneous minimization of surface roughness, cutting force and delamination factor. Experiments were planned using Taguchi’s orthogonal array with the machining parameters, namely, helix angle of the end mill cutter, spindle speed, feed rate and depth of cut were optimized with considerations of multiple response characteristics, including machining force, surface roughness and delamination as the responses. PCA is adopted to find the weight factors involved for all objectives. Finally analysis of variance concept is employed on multi-SN ratio to find out the relative significance of machining parameter in terms of their percentage contribution.FindingsThe multi-SN ratio is achieved by the product of weight factor and SN ratio to the performance characteristics in the utility concept. The results show that a combination of machining parameters for the optimized results has helix angle of 35°, machining speed of 4,000 m/min, feed rate of 750 mm/rev and depth of cut of 2.0 mm.Originality/valueEffect of milling of GFRP composites on delamination factor, surface roughness and machining force with various helix angle solid carbide end mill has not been analysed yet using PCA techniques.

Journal

Multidiscipline Modeling in Materials and Structures – Emerald Publishing

Published: Jun 12, 2017

There are no references for this article.