NDLI: Selection of optimum cutting condition of cobalt-based superalloy with GONNS

Content Provider	Springer Nature Link
Author	Aykut, Şeref Demetgul, Mustafa Tansel, Ibrahim N.
Copyright Year	2009
Abstract	Machining of new superalloys is challenging. Automated software environments for determining the optimal cutting conditions after reviewing a set of experimental results are very beneficial to obtain the desired surface quality and to use the machine tools effectively. The genetically optimized neural network system (GONNS) is proposed for the selection of optimal cutting conditions from the experimental data with minimal operator involvement. Genetic algorithm (GA) obtains the optimal operational condition by using the neural networks. A feed-forward backpropagation-type neural network was trained to represent the relationship between surface roughness, cutting force, and machining parameters of face-milling operation. Training data were collected at the symmetric and asymmetric milling operations by using different cutting speeds (V c), feed rates (f), and depth of cuts (a p) without using coolant. The surface roughness (Raasymt, Rasymt) and cutting force (Fxasymt, Fyasymt, Fzasymt, Fxsymt, Fysymt, Fzsymt) were measured for each cutting condition. The surface roughness estimation accuracy of the neural network was better for the asymmetric milling operation with 0.4% and 5% for training and testing data, respectively. For the symmetric milling operations, slightly higher estimation errors were observed around 0.5% and 7% for the training and testing. One parameter was optimized by using the GONNS while all the other parameters, including the cutting forces and the surface roughness, were kept in the desired range.
Starting Page	957
Ending Page	967
Page Count	11
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	46
Issue Number	9-12
e-ISSN	14333015
Language	English
Publisher	Springer-Verlag
Publisher Date	2009-06-24
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Surface roughness Cutting forces Surface milling Stellite 6 CNC milling Artificial neural networks GONN Genetic algorithm Computer-Aided Engineering (CAD, CAE) and Design Mechanical Engineering Production/Logistics Industrial and Production Engineering
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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