Multi response prediction of cutting force and delamination in carbon fiber reinforced polymer using backpropagation neural network-genetic algorithm

Fathi Robbany*, Bambang Pramujati, Suhardjono, Mohammad Khoirul Effendi, Bobby Oedy Pramoedyo Soepangkat, Rachmadi Norcahyo

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

Carbon Fiber Reinforced Polymer (CFRP) has been widely used in various industries, including automotive, trains, and especially aerospace as a substitute for metal materials because of its high specific strength. Milling is one of the most commonly used machining processes in composites. Thus, it is necessary to determine the exact machining process parameters so that the specifications of the components are met. Moreover, suitable optimization method is needed to obtain machining parameters that produce small delamination and low cutting force. Full factorial design (2x3x3) with spindle speed, cutting speed and depth of cut as an input and the responses of cutting force and delamination was carried out in this experiment. A genetic algorithm was used as an optimization method, while backpropagation neural networks (BPNN) were used to apply complex non-linear equations. The BPNN model optimized using the GA method has been successfully developed in which the end milling process on CFRP material gains a mean square error (MSE) of 0.0246. This value indicates that the BPNN-GA model can be used as a predictor of the end milling CFRP process and eventually used to optimize the machining process.

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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