Modelling and Optimization of Process Parameters affecting machining involved in Electric Discharge Machining by GA-ANN

Shadab Ahmad; Praveen; Prateek; Prateek Kalyani; Ranganath M. S.; R. S. Mishra; Md Jamil Akhtar

doi:https://doi.org/10.51976/ijari.641812

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Modelling and Optimization of Process Parameters affecting machining involved in Electric Discharge Machining by GA-ANN

Shadab Ahmad, Praveen , Prateek , Prateek Kalyani, Ranganath M. S., R. S. Mishra, Md Jamil Akhtar

Vol 6 , Issue 4 , October - December 2018 | Pages: 107-116 | Research Paper

https://doi.org/10.51976/ijari.641812

Received: October 07, 2018 | Revised: October 28, 2018 | Accepted: November 02, 2018 | Published Online: December 15, 2018

Author Details ( * ) denotes Corresponding author

1. * Shadab Ahmad, Department of Mechanical, Production & Industrial and Automobiles, Engineering, Delhi Technological University, Delhi, India (sheo2008@gmail.com)

2. Praveen Department of Mechanical, Production & Industrial and Automobiles, Engineering, Delhi Technological University, Delhi, India

3. Prateek Department of Mechanical, Production & Industrial and Automobiles, Engineering, Delhi Technological University, Delhi, India

4. Prateek Kalyani, Department of Mechanical, Production & Industrial and Automobiles, Engineering, Delhi Technological University, Delhi, India

5. Ranganath M. S., Department of Mechanical, Production & Industrial and Automobiles, Engineering, Delhi Technological University, Delhi, India

6. R. S. Mishra, Department of Mechanical, Production & Industrial and Automobiles, Engineering, Delhi Technological University, Delhi, India

7. Md Jamil Akhtar, Department of Mechanical, Production & Industrial and Automobiles, Engineering, Delhi Technological University, Delhi, India

Electric Discharge Machining process is one of the earliest and most extensively used unconventional machining process. It is a non-contact machining process that uses a series of electric discharges to remove material from an electrically conductive workpieces. The EDM process parameter are pulse on time, duty factor, peak current, peak voltage, flushing pressure. This study is aimed to do a comprehensive study of the EDM, develop a model that can predict the machining characteristic and then optimize the output parameters. Artificial Neural Network processes the information by transferring the data between its basic building block i.e. Artificial Neuron. Genetic algorithm is a metaheuristic technique used to find the best fit and approximate solutions to optimization and search problems. In this project we proposed a GA-ANN hybrid model. Also comparison is studied the experimental values and ANN predicted values. GA-ANN model concludes that the error calculated in experimental values V/S ANN-GA predicted values is very less compared to experimental values V/S ANN predicted values

Keywords

Electric Discharge Machine; Optimization; Artificial Neural Networks.

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