Neuro-fuzzy model and regression model a comparison study of MRR in electrical discharge machining of D2 tool steel

• Main Authors: Pradhan, M.K., Biswas, C.K.
• Format: Article
• Published: 2009
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://www.scopus.com/inward/record.url?eid=2-s2.0-84871114676&partnerID=40&md5=190f3109d9370626ff7f636f354e347c; http://eprints.utp.edu.my/10070/

In the current research, neuro-fuzzy model and regression model was developed to predict Material Removal Rate in Electrical Discharge Machining process for AISI D2 tool steel with copper electrode. Extensive experiments were conducted with various levels of discharge current, pulse duration and duty cycle. The experimental data are split into two sets, one for training and the other for validation of the model. The training data were used to develop the above models and the test data, which was not used earlier to develop these models were used for validation the models. Subsequently, the models are compared. It was found that the predicted and experimental results were in good agreement and the coefficients of correlation were found to be 0.999 and 0.974 for neuro fuzzy and regression model respectively.