DEVELOPMENT OF MODELS USING GENETIC PROGRAMMING FOR TURNING INCONEL 718 WITH COATED CARBIDE TOOLS

This paper discusses the methodology of developing models for the turning process for machining Inconel 718 alloy with coated carbide tool inserts. Approach through Genetic programming (GP) was aimed at with an overall objective of optimizing the process to yield higher metal removal, better surface quality and lower cutting forces. Taguchi's approach was adopted for the design of experiments and accordingly experiments were carried out, for collecting experimental data in a controlled manner. Such data was grouped separately at random for training genetic models (the models developed using GP) and further validating them. Models generated establish relationship between the input parameters with the output parameter and also show the order of dominance of the input parameters. Prediction of the output parameters is in fair comparison with the actual measured values. For easy understanding and explicit depiction, plots were made for each output parameter. Plots made show the trend of the prediction capability of the models in both the training set and validation set of data; further the plots exhibit the trend of variables' interaction in the process. This work resulted in developing models for the turning process for Inconel 718 Alloy in a scientific manner. It also enables identifying the optimised set of turning parameters for Inconel 718 material using coated carbide tools, to achieve better surface roughness and higher material removal. This work gains significance in the sense with reasonably minimum number of experiments, reliable model has been generated, validated and further, the process has been optimised with two objectives (viz. improved quality and higher productivity).