An integrated ANN – PSO approach to optimize the material removal rate and surface roughness of wire cut EDM on INCONEL 750

This investigation was planned to get the optimized material removal rate and surface finish of Wire Cut Electric Discharge Machining (WEDM) on Inconel 750 by taking into consideration of four input factors such as Pulse On, Pulse Off, Voltage and Current. Taguchi supported L9 orthogonal array was u...

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Bibliographic Details
Main Authors: Naveen Babu, K., Karthikeyan, R., Punitha, A.
Format: Conference Proceeding
Language:English
Subjects:
ANN
Inconel 750
PSO
Surface roughness
Wire cut EDM
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Summary:This investigation was planned to get the optimized material removal rate and surface finish of Wire Cut Electric Discharge Machining (WEDM) on Inconel 750 by taking into consideration of four input factors such as Pulse On, Pulse Off, Voltage and Current. Taguchi supported L9 orthogonal array was used to determine the total number of experimental conditions and its values of material removal rate were calculated. To optimize the material removal rate and surface roughness, a feed forward artificialneural network model was developed and particle swarm optimization was used by optimizing the weighing factors of the network in the neural power software. Finally, the model was achieved with the root mean square error of 0.0053881 and 0.0038324 for MRR and SR respectively. Moreover, the optimized MRR and SR were obtained 22.11 mm3/min and 2.33 μm respectively.
ISSN:2214-7853
2214-7853
DOI:10.1016/j.matpr.2019.07.643