Predicting material removal rate of Electrical Discharge Machining (EDM) using artificial neural network for high Igap current
This article presents a prediction of Material Removal Rate (MRR) in Electrical Discharge Machining (EDM) using Artificial Neural Network (ANN). Experimental data were gathered from Die sinking EDM process for copper-electrode and steel-workpiece. It is aimed to develop a behavioral model using inpu...
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| Format: | Book Section |
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IEEE Explorer
2011
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| _version_ | 1796856532205305856 |
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| author | Yahya, Azli Khamis, Nor Hisham Khalil, Kamal Erawan, Ade Andromeda, Trias |
| author_facet | Yahya, Azli Khamis, Nor Hisham Khalil, Kamal Erawan, Ade Andromeda, Trias |
| author_sort | Yahya, Azli |
| collection | ePrints |
| description | This article presents a prediction of Material Removal Rate (MRR) in Electrical Discharge Machining (EDM) using Artificial Neural Network (ANN). Experimental data were gathered from Die sinking EDM process for copper-electrode and steel-workpiece. It is aimed to develop a behavioral model using input-output pattern of raw data from EDM process experiment. The behavioral model is used to predict MRR and than the predicted MRR is compared to actual MRR value. The results show good agreement of predicting MRR between them. |
| first_indexed | 2024-03-05T18:44:27Z |
| format | Book Section |
| id | utm.eprints-29317 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T18:44:27Z |
| publishDate | 2011 |
| publisher | IEEE Explorer |
| record_format | dspace |
| spelling | utm.eprints-293172017-02-05T00:10:33Z http://eprints.utm.my/29317/ Predicting material removal rate of Electrical Discharge Machining (EDM) using artificial neural network for high Igap current Yahya, Azli Khamis, Nor Hisham Khalil, Kamal Erawan, Ade Andromeda, Trias TK Electrical engineering. Electronics Nuclear engineering This article presents a prediction of Material Removal Rate (MRR) in Electrical Discharge Machining (EDM) using Artificial Neural Network (ANN). Experimental data were gathered from Die sinking EDM process for copper-electrode and steel-workpiece. It is aimed to develop a behavioral model using input-output pattern of raw data from EDM process experiment. The behavioral model is used to predict MRR and than the predicted MRR is compared to actual MRR value. The results show good agreement of predicting MRR between them. IEEE Explorer 2011 Book Section PeerReviewed Yahya, Azli and Khamis, Nor Hisham and Khalil, Kamal and Erawan, Ade and Andromeda, Trias (2011) Predicting material removal rate of Electrical Discharge Machining (EDM) using artificial neural network for high Igap current. In: InECCE 2011 - International Conference on Electrical, Control and Computer Engineering. IEEE Explorer, Pahang, Malaysia, 259 - 262. ISBN 978-1-61284-229-5 http://dx.doi.org/10.1109/INECCE.2011.5953887 10.1109/INECCE.2011.5953887 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Yahya, Azli Khamis, Nor Hisham Khalil, Kamal Erawan, Ade Andromeda, Trias Predicting material removal rate of Electrical Discharge Machining (EDM) using artificial neural network for high Igap current |
| title | Predicting material removal rate of Electrical Discharge Machining (EDM) using artificial neural network for high Igap current |
| title_full | Predicting material removal rate of Electrical Discharge Machining (EDM) using artificial neural network for high Igap current |
| title_fullStr | Predicting material removal rate of Electrical Discharge Machining (EDM) using artificial neural network for high Igap current |
| title_full_unstemmed | Predicting material removal rate of Electrical Discharge Machining (EDM) using artificial neural network for high Igap current |
| title_short | Predicting material removal rate of Electrical Discharge Machining (EDM) using artificial neural network for high Igap current |
| title_sort | predicting material removal rate of electrical discharge machining edm using artificial neural network for high igap current |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
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