International Journal of Mechanical and Production Engineering (IJMPE)
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Statistics report
Apr. 2021
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 94
Paper Published : 2094
No. of Authors : 5972
  Journal Paper


Paper Title :
Adaptive Network-Based Fuzzy Inference System (ANFIS) Application on Modeling of Glass/Epoxy Composites for Drilling Operation

Author :Semih Ozden, Ahmet Mavi

Article Citation :Semih Ozden ,Ahmet Mavi , (2019 ) " Adaptive Network-Based Fuzzy Inference System (ANFIS) Application on Modeling of Glass/Epoxy Composites for Drilling Operation " , International Journal of Mechanical and Production Engineering (IJMPE) , pp. 29-33, Volume-7,Issue-12

Abstract : In this study, machine learning algorithm performed for modelling of drilling operation on Glass/epoxy composites. This material uses several industrial applications especially it has crucial for defense industry. In this sector, one of the most widely used manufacturing methods is the drilling process. Thus, thrust force and moment on drilling operations was modelled by using ANFIS method. Input parameters of model are cutting speed, feed rate and the ratio of carbon nanotubes. The results show that force and moment could be modelled by ANFIS. Training errors for force and moment are both lower than 1e-6 and checking (validation) errors are 0,363765 and 0,369569, respectively. Keywords - Drilling, Glass/Epoxy Composite, ANFIS, Optimization

Type : Research paper

Published : Volume-7,Issue-12


DOIONLINE NO - IJMPE-IRAJ-DOIONLNE-16717   View Here

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