Design of genetic-fuzzy expert system for predicting surface finish in ultra-precision diamond turning of metal matrix composite

In this work, an attempt has been made to design an expert system using two soft computing tools, namely fuzzy logic and genetic algorithm, so that the surface finish in ultra-precision diamond turning of metal matrix composite can be modeled for set of given cutting parameters, namely spindle speed, feed rate and depth of cut. In the proposed system, an optimized knowledge base of the fuzzy expert system is obtained using a binary-coded genetic algorithm. As genetic algorithm (GA) is computationally expensive, the GA based training is done off-line. Once trained, the GA-trained fuzzy expert system (GAFES) will be able to predict surface finish in ultra-precision diamond turning of Al6061/SiCp metal matrix composite before conducting actual experiment. The predicted surface finish values obtained from GAFES were compared with the experimental data. The comparison indicates that the proposed system can produce efficient knowledge base of fuzzy expert system for predicting the surface finish in diamond turning.