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Fuzzy Logic Based Model For Predicting Surface Roughness Of Machined Al-Si-Cu-Fe Die Casting Alloy Using Different Additives-Turning
Faculty of Engineering University of Malaya
This paper presents a fuzzy logic artificial intelligence technique for predicting the machining performance of Al-Si-Cu-Fe die casting alloy treated with different additives including strontium, bismuth and antimony to improve surface roughness. The Pareto-ANOVA optimization method was used to obtain the optimum parameter conditions for the machining process. Experiments were carried out using oblique dry CNC turning. The machining parameters of cutting speed, feed rate and depth of cut were optimized according to surface roughness values. The results indicated that a cutting speed of 250 m/min, a feed rate of 0.05 mm/rev, and a depth of cut of 0.15 mm …