Identification of Optimal Process Parameters in Electro-Discharge Machining Using ANN and PSO

Identification of Optimal Process Parameters in Electro-Discharge Machining Using ANN and PSO

Copyright: © 2022 |Pages: 19
ISBN13: 9781668424087|ISBN10: 1668424088|EISBN13: 9781668424094
DOI: 10.4018/978-1-6684-2408-7.ch038
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MLA

Kumar, Kaushik, and J. Paulo Davim. "Identification of Optimal Process Parameters in Electro-Discharge Machining Using ANN and PSO." Research Anthology on Artificial Neural Network Applications, edited by Information Resources Management Association, IGI Global, 2022, pp. 824-842. https://doi.org/10.4018/978-1-6684-2408-7.ch038

APA

Kumar, K. & Davim, J. P. (2022). Identification of Optimal Process Parameters in Electro-Discharge Machining Using ANN and PSO. In I. Management Association (Ed.), Research Anthology on Artificial Neural Network Applications (pp. 824-842). IGI Global. https://doi.org/10.4018/978-1-6684-2408-7.ch038

Chicago

Kumar, Kaushik, and J. Paulo Davim. "Identification of Optimal Process Parameters in Electro-Discharge Machining Using ANN and PSO." In Research Anthology on Artificial Neural Network Applications, edited by Information Resources Management Association, 824-842. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-6684-2408-7.ch038

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Abstract

Electrical Discharge Machining (EDM) process is a widely used machining process in several fabrication, construction and repair work applications. Considering Pulse-On Time, Pulse OFF time, Peak-Current and Gap voltage as the inputs and among all possible outputs, in the present work Material Removal Rate and Surface Roughness are considered as outputs. In order to reduce the number of experiments Design of Experiments (DOE) was undertaken using Orthogonal Array and later on the outputs were optimized using ANN and PSO. It was found that the results obtained from both the techniques were tallying with each other.

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