Artificial neural network models for the prediction of surface roughness in electrical discharge machining

In the present paper Artificial Neural Networks (ANNs) models are proposed for the prediction of surface roughness in Electrical Discharge Machining (EDM). For this purpose two well-known programs, namely Matlab ® with associated toolboxes, as well as Netlab ® , were emplo- yed. Training of the mode...

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Bibliographic Details
Published in:Journal of intelligent manufacturing 2008-06, Vol.19 (3), p.283-292
Main Authors: Markopoulos, Angelos P., Manolakos, Dimitrios E., Vaxevanidis, Nikolaos M.
Format: Article
Language:English
Subjects:
Algorithms
Brain
Business and Management
Control
Data compression
Machines
Manufacturing
Mechanical engineering
Mechatronics
Neural networks
Neurons
Process planning
Processes
Production
Robotics
Steel
Surface roughness
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Summary:In the present paper Artificial Neural Networks (ANNs) models are proposed for the prediction of surface roughness in Electrical Discharge Machining (EDM). For this purpose two well-known programs, namely Matlab ® with associated toolboxes, as well as Netlab ® , were emplo- yed. Training of the models was performed with data from an extensive series of EDM experiments on steel grades; the proposed models use the pulse current, the pulse duration, and the processed material as input parameters. The reported results indicate that the proposed ANNs models can satisfactorily predict the surface roughness in EDM. Moreover, they can be considered as valuable tools for the process planning for EDMachining.
ISSN:0956-5515
1572-8145
DOI:10.1007/s10845-008-0081-9