Artificial Neural Network prediction model for MRR in WEDM of WC-Co - Sable, Yogesh; Dharmadhikari, H.M. (Materials today : proceedings, 2023)
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.