The compliance of an integrated approach, principal component analysis(PCA),coupled with Taguchi’s robust theory for simultaneous optimization of correlated multiple responses of wire electrical discharge machining(WEDM) process for machining SiC_P reinforced ZC63 metal matrix composites(MMCs) is investigated in this work.The WEDM is proven better for its efficiency to machine MMCs among others,while the particulate size and volume percentage of SiC_p with the composite are the utmost important factors.These improve the mechanical properties enormously,however reduce the machining performance.Hence the WEDM experiments are conducted by varying the particulate size,volume fraction,pulse-on time,pulse-off time and wire tension.In the view of quality cut,the most important performance indicators of WEDM as surface roughness(R_a),metal removal rate(MRR),wire wear ratio(WWR),kerf(K_w) and white layer thickness(WLT) are measured as responses.PCA is used as multi-response optimization technique to derive the composite principal component(CPC) which acts as the overall quality index in the process.Consequently, Taguchi’s S/N ratio analysis is applied to optimize the CPC. The derived optimal process responses are confirmed by the experimental validation tests results.The analysis of variance is conducted to find the effects of choosing process variables on the overall quality of the machined component. The practical possibility of the derived optimal process conditions is also presented using SEM. The compliance of an integrated approach, principal component analysis (PCA), coupled with Taguchi’s robust theory for simultaneous optimization of correlated responses of wire electrical discharge machining (WEDM) process for machining SiC_P reinforced ZC63 metal matrix composites (MMCs) is investigated in this work.The WEDM is proven better for its efficiency to machine MMCs among others, while the particulate size and volume percentage of SiC_p with the composite are the utmost important factors .sese improve the mechanical properties enormously but reduce the machining performance .ence the WEDM experiments are conducted by varying the particulate size, volume fraction, pulse-on time, pulse-off time and wire tension. the view of quality cut, the most important performance indicators of WEDM as surface roughness (R_a), metal removal rate ( MRR), wire wear ratio (WWR), kerf (K_w) and white layer thickness (WLT) are measured as responses. PCA is used as multi-response optimization techniq The derived optimal process responses are confirmed by the experimental validation tests results. The analysis of variance is conducted to find the effects of choosing process variables on the overall quality of the machined component. The practical possibility of the derived optimal process conditions is also presented using SEM.