Application of grey fuzzy logic for the optimization of CNC milling parameters for Al–4.5%Cu–TiC MMCs with multi-performance characteristics

Abstract

With the major application of MMCs, it is thus necessary to develop an appropriate technology for their efficient machining. Milling is the most common and versatile technology among different machining processes, characterized by an extensive range of metal cutting capacity that places it in a central role in the manufacturing industries. In the present study an attempt has been made to find out the most optimal level of process parameters for CNC milling of Al–4.5%Cu–TiC metal matrix composites using grey-fuzzy algorithm. Taguchi's L25 orthogonal array design is used for performing CNC milling operation on the composite plates. The Grey fuzzy optimization of CNC milling parameters consist of three different output characteristics; such as, cutting force Fc, surface roughness Ra and surface roughness Rz. It was found that a cutting speed of 600 rpm, feed of 40 mm/min and a depth of cut of 0.30 mm is the optimal combination of CNC milling parameters that has produced a high value of grey fuzzy reasoning grade of 0.8191 which is close to the reference value. ANOVA analysis is carried out and it is found that among three different process parameters, the cutting speed played a major role on the determination of GFRG.