Optimization of Process Parameter for Turning of Nimonic 263 using Dry and Flood Cooling.

Abstract

This study presents an experimental investigation on the machining performance of Nimonic 263 under dry and flood cooling conditions using the Taguchi method and Grey Relational Analysis (GRA). The experiments were designed using an L9 orthogonal array considering cutting speed, feed rate, and depth of cut as input parameters, while surface roughness (Ra) and cutting zone temperature (CZT) were taken as performance characteristics. Multi-response optimization was carried out using GRA by converting multiple responses into a single Grey Relational Grade (GRG). The results indicate that depth of cut is the most significant factor affecting machining performance, followed by feed rate and cutting speed. The optimum parameter combination for dry machining was 50 m/min cutting speed, 0.35 mm/rev feed rate and 0.5 mm depth of cut, whereas flood cooling achieved optimum performance at 80 m/min cutting speed, 0.35 mm/rev feed rate and 0.5 mm depth of cut. Confirmation experiments validated the optimization results, showing good agreement between predicted and experimental GRG values with prediction error of 6.89 % under dry and 3.67% under flood cooling.  The study concludes that while optimized dry machining can yield acceptable results, flood cooling provides superior performance in machining Nimonic 263....