COMBINED DESIGN OF EXPERIMENTS AND FUZZY LOGIC APPLICATION TO PREDICT SURFACE ROUGHNESS AND MATERIAL REMOVAL RATE ON CNC TURNING

Abstract

Turning is an important machining operation which is widely applied in industrial applications. So it is important to study turning process at different cutting conditions in order to find out the optimum solution for any particular material which results in best results. Lots of studies have been carried out on the same on different materials at various parameters in the past. In present study AISI1040 (EN8) steel is used as work piece material as it has wide industrial applications viz. shafts, gears, stressed pins, bolts, keys etc. There are lots of machining parameters which affects the output parameters but from the literature study it has been found that cutting speed, feed rate and depth of cut has a great impact and same has been adopted as input parameters for the current study. Surface finish and material removal rate are the output parameters. Experiments have been carried out on HMT made Pushkar 200 lathe machine at different input parameters and corresponding output response is monitored and tabled. Surface finish is measured with the help of Tecnai G2 20 (Fei) S-Twin roughness tester. Material removal rate must be high and surface finish to be minimum possible so ‘Large the best’ and ‘Small the best’ is chosen respectively in Taguchi technique. In order to optimize the output response design of experiment techniques, S/N ratio, ANOVA, Taguchi methodology and fuzzy logic have been used. Results have been optimized with the help of Minitab and Matlab software. From the experimental analysis and application of optimization techniques it has been found that feed rate is most influencing factor followed by cutting speed and depth of cut in case of surface finish. In case of MRR, feed rate is most influencing factor followed by depth of cut and cutting speed.