Multi-objective optimization of CFRP drilling parameters with a hybrid method integrating the ANN, NSGA-II and fuzzy C-means

A full factorial experiment is performed for the conventional dry drilling of CFRP with spindle speed, feed rate and point angle as drilling parameters, response variables are thrust force and exit-delamination. Artificial neural network (ANN) is developed to express thrust force and delamination fa...

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Bibliographic Details

Published in:	Composite structures Vol. 235; p. 111803
Main Authors:	Wang, Qian, Jia, Xiaoliang
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.03.2020
Subjects:	Artificial neural network (ANN) Carbon fiber reinforced polymer Fuzzy C-means clustering algorithm Multi-objective optimization Non-dominated Sorting Genetic Algorithm (NSGA-II) Fuzzy C-means clustering algorithm Multi-objective optimization Artificial neural network (ANN) Carbon fiber reinforced polymer Non-dominated Sorting Genetic Algorithm (NSGA-II)
ISSN:	0263-8223, 1879-1085
Online Access:	Get full text
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