Abstract

Devendra Kashyap, Sagar Gupta, Avinash Bhardwaj, Sanjay Vaidhya

ABSTRACT

Industrial productivity, respecting the general rules of work and ecology of the environment system by avoiding several types of machining, research is directed towards the steels with improved machinability and coating cutting tools. Design of experiment obtained through Full Factorial design, a total of 27 tests were carried out and optimum level for MRR and cutting force were chosen from the three levels of cutting parameters considered. The experimental data’s are later used to predict output data by using artificial neural network. Neural network algorithms are developed for use as a direct modeling method, to predict MRR only for machining parameters. Prediction of MRR is often needed in order to establish result forecasting of the machining processes. The neural network design and development was done using MATLAB.