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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Bibliographic Details
Published inMaterials today : proceedings Vol. 72; pp. 1650 - 1656
Main Authors Sable, Yogesh, Dharmadhikari, H.M.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 2023
Subjects
ANN
Material removal rate
WC-Co
WEDM
ANN
Material removal rate
WC-Co
WEDM
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ISSN2214-7853
2214-7853
DOI10.1016/j.matpr.2022.09.444

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Summary: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.
ISSN:2214-7853
2214-7853
DOI:10.1016/j.matpr.2022.09.444