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Multiple performance optimization in machining of GFRP composites by a PCD tool using non-dominated sorting genetic algorithm (NSGA-II)

Content Provider	Springer Nature Link
Author	Palanikumar, K. Latha, B. Senthilkumar, V. S. Karthikeyan, R.
Copyright Year	2009
Abstract	Optimization of cutting parameters is important to achieving high quality in the machining process, especially where more complex multiple performance optimization is required. The present investigation focuses on the multiple performance optimization on machining characteristics of glass fiber reinforced plastic (GFRP) composites. The cutting parameters used for the experiments, which were carried out according to Taguchi’s L$_{27}$, 3-level orthogonal array, were cutting speed, feed and depth of cut. Statistical models based on second-order polynomial equations were developed for the different responses. The Non-dominated Sorting Genetic Algorithm (NSGA-II) tool was used to optimize the cutting conditions, yielding a non-dominated solution set that is reported here.
Starting Page	249
Ending Page	258
Page Count	10
File Format	PDF
ISSN	15989623
Journal	Metals and Materials
Volume Number	15
Issue Number	2
e-ISSN	20054149
Language	English
Publisher	The Korean Institute of Metals and Materials
Publisher Date	2009-05-28
Publisher Place	Springer
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	GFRP composites turning modeling optimization non-dominated sorting genetic algorithm (NSGA-II) Continuum Mechanics and Mechanics of Materials Characterization and Evaluation of Materials Engineering Thermodynamics, Heat and Mass Transfer Magnetism, Magnetic Materials Operating Procedures, Materials Treatment Metallic Materials
Content Type	Text
Resource Type	Article
Subject	Materials Chemistry Mechanics of Materials Metals and Alloys Condensed Matter Physics

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