A grey and fuzzy algorithms integrated approach to the optimization of turning Hadfield steel with Al2O3/TiC mixed ceramic tool

This paper focuses on the development of a fast and effective algorithm to determine the optimum manufacturing conditions for turning Hadfield steel with Al2O3/TiC mixed ceramic tool by coupling the grey relational analysis with the fuzzy logic. The flank wear and surface roughness were adopted to evaluate the machiniablity performances. Various cutting parameters, such as cutting speed, feed rate, depth of cut and nose radius of tool were explored by experiment. An orthogonal array was employed for the experimental design. This proposed algorithm obtains a grey–fuzzy reasoning grade to evaluate the multiple performance characteristics through the grey relational coefficient of each performance characteristic. The response table, response graph and analysis of variance (ANOVA) were used to find the optimal levels and the effect of cutting parameters on the flank wear and surface roughness. A confirmation test within the optimal machining parameters was conducted to indicate the effectiveness of this proposed algorithm. Experimental results have shown that the required performance characteristics in the turning process have great improvements through this proposed algorithm.