Machining with aluminum is a tedious task due to its tendency of forming on cutting tool as a built-up edge, leading in the direction of deteriorated surface finish. These cutting parameters have to be chosen cleverly so that the problem can be resolved. The present work is an attempt for reducing the input process variables for making superior solution to optimize the material removal rate (MRR) also surface roughness (Ra) during high-speed turning of Al7175/SiC/Al₂O₃ nanoparticles with coated cemented carbide insert. These studies are performed on a speed lathe. Accordingly, the levels are three, that are cutting speed, feed, and depth of cut be present in use and Taguchi design the experiments. The process performance was analyzed during expressions with specimen surface roughness produced, along with rate of specimen materials removed at the time of machining. Regression equations were formed and the factorial graphs along with response surfaces were analyzed. this is happened to this selected range of machine input variables the specimen exterior surface irregularity deceased with increase with both speed and feed whereas it first decreased among enhance with cutting depth also subsequently started increasing again. Similarly, the tool flank wear first decreased and then started increasing again with increase in feed. Also, it decreased with the increase in cutting speed. This material removal on work specimen always enhances among raises with value of process parameters. These methods of input variables for cutting were proposed for optimized process performance in terms of surface roughness and MRR.

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