Abstract

Carbon Fiber Reinforced Polymer (CFRP) composite material has been widely used in various applications, especially in the field of aerospace and aviation, automotive, maritime, and sports equipment manufacturing. CFRP is replacing conventional materials with excellent strength and low specific weight properties. Manufacturing capabilities in a variety of combinations with adjustable strength properties, high fatigue, high toughness and temperature resistance and oxidation resistance capability make this material an excellent choice in engineering applications. As in machining all anisotropic and heterogeneous materials, the failure mechanism also occurs in the machining of CFRP materials. In this research, we conduct End milling machining parameter optimization on CFRP using Back Propagation Neural Network (BPNN) and Genetic Algorithm (GA) to predict the final factory process response. The experiment is carried out with a complete factorial design with 18 combinations (2 x 3 x 3), full factorial use so that we could collect more data, which would improve the accuracy of neural network training results. The measured response is cutting force and surface roughness. From the results of the genetic algorithm, we find that the most optimal network structure is 2 hidden layers with 10 x 2 nodes in each layer. While the prediction error using BPNN is 0.0073%. We conclude that this network structure is capable of predicting the response well so that it can be used to optimize the machining parameters in the CFRP end milling.

Original languageEnglish
Title of host publicationExploring Resources, Process and Design for Sustainable Urban Development
Subtitle of host publicationProceedings of the 5th International Conference on Engineering, Technology, and Industrial Application, ICETIA 2018
EditorsWisnu Setiawan, Nur Hidayati, Anto Budi Listyawan, Nurul Hidayati, Hari Prasetyo, Munajat Tri Nugroho, Tri Widodo Besar Riyadi
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735418509
DOIs
Publication statusPublished - 26 Jun 2019
Event5th International Conference on Engineering, Technology, and Industrial Application: Exploring Resources, Process and Design for Sustainable Urban Development, ICETIA 2018 - Surakarta, Central Java, Indonesia
Duration: 12 Dec 201813 Dec 2018

Publication series

NameAIP Conference Proceedings
Volume2114
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference5th International Conference on Engineering, Technology, and Industrial Application: Exploring Resources, Process and Design for Sustainable Urban Development, ICETIA 2018
Country/TerritoryIndonesia
CitySurakarta, Central Java
Period12/12/1813/12/18

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