Mechanical Engineering, Arunachala College of Engineering for Women, Kanyakumari, Tamilnadu, India
Mechanical Engineering, Hindustan University, Chennai
Mechanical Engineering, Mar Ephraem College of Engineering and Technology
The tool wear is an unavoidable phenomenon when using coated carbide tools during hard turning of hardened steels. This work focuses on the prediction of tool wear using regression analysis and artificial neural network (ANN).The work piece taken into consideration is AISI4140 steel hardened to 47 HRC. The models are developed from the results of experiments, which are carried out based on Design of experiments (Response surface methodology). The cutting speed, feed and depth of cut are taken as the inputs and the wear is the output. The results reveal that the ANN provides better accuracy when compared to Regression analysis.