In this study, investigation on machinability characteristic of aluminum silicon carbide composite on electrical discharge machine is carried out. The composites are prepared through powder metallurgy route. The influence of four machining parameters (discharge current, pulse duration, duty cycle, and flushing pressure) and two material parameters (weight fraction of silicon carbide in the composite and mesh size) on selected responses are studied. The responses considered, in this work, are material removal rate, tool wear rate, surface roughness and circularity. In actual machining application, it is desirable to find a parametric combination that leads to simultaneous optimization of all the responses. Classical Taguchi method can optimize a single response but not multiple responses. In order to simultaneously optimize multiple responses, a hybrid approach combining principal component analysis (PCA) and fuzzy inference system is coupled with Taguchi method. The influence of each parameter on the responses is established using analysis of variances (ANOVA) at 5% level of significance. It is found that pulse duration, duty cycle, discharge current and flushing pressure contribute significantly to the multiple performance characteristic index. The four responses at optimal parameter setting have been reported. © 2013 Elsevier Ltd. All rights reserved.