Artificial Neural Network prediction model for MRR in WEDM of WC-Co
The studied work aimed to develop the predictive models of removal rate of WC-Co composite material in WEDM. Back prorogation algorithm of ANN is used to predict the MRR in WEDM of WC-Co. The training and testing data were collected by performing WEDM experiments on work piece material of WC-Co as p...
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| Published in | Materials today : proceedings Vol. 72; pp. 1650 - 1656 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
2023
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2214-7853 2214-7853 |
| DOI | 10.1016/j.matpr.2022.09.444 |
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| Abstract | The studied work aimed to develop the predictive models of removal rate of WC-Co composite material in WEDM. Back prorogation algorithm of ANN is used to predict the MRR in WEDM of WC-Co. The training and testing data were collected by performing WEDM experiments on work piece material of WC-Co as per FCC composite design, containing five control factors like peak current, wire tension, pulse on-duration, servo voltage and pulse off-duration, and material removal rate were considered as the performance measure. ANN model has been developed with less than 0.05 error and correlation coefficient R2 of testing-0.95871 and validation-0.9968 to forecast the value of MRR. |
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| AbstractList | The studied work aimed to develop the predictive models of removal rate of WC-Co composite material in WEDM. Back prorogation algorithm of ANN is used to predict the MRR in WEDM of WC-Co. The training and testing data were collected by performing WEDM experiments on work piece material of WC-Co as per FCC composite design, containing five control factors like peak current, wire tension, pulse on-duration, servo voltage and pulse off-duration, and material removal rate were considered as the performance measure. ANN model has been developed with less than 0.05 error and correlation coefficient R2 of testing-0.95871 and validation-0.9968 to forecast the value of MRR. |
| Author | Dharmadhikari, H.M. Sable, Yogesh |
| Author_xml | – sequence: 1 givenname: Yogesh surname: Sable fullname: Sable, Yogesh email: yssablejnec@gmail.com organization: Department of Mechanical Engineering, Jawaharlal Nehru Engineering College, Aurangabad 431005, MS, India – sequence: 2 givenname: H.M. surname: Dharmadhikari fullname: Dharmadhikari, H.M. organization: Department of Mechanical Engineering, Marathwada Institute of Technology, Aurangabad 431005, MS, India |
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| Cites_doi | 10.1016/j.precisioneng.2021.08.018 10.1007/s13198-020-00990-z 10.1016/j.mspro.2014.07.205 10.1007/s00170-010-2653-z 10.1081/AMP-200055033 10.1016/j.procir.2013.01.003 10.15373/2249555X/MAY2013/66 10.1007/s00170-004-2203-7 10.1080/10426910903365760 10.1109/INECCE.2011.5953887 |
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| Title | Artificial Neural Network prediction model for MRR in WEDM of WC-Co |
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