Application Of WPCA & CQL Methods In The Optimization Of Mutiple Responses

Abstract

Abstract In this work, an investigational study has been carried out to optimize the multiple responses of the material removal rate (MRR) and surface roughness parameters (Ra, Rq and Rz). The investigating experiments were done with the CNC turret machine according to the standard Taguchi's L9 orthogonal exhibit plan. Cutting velocity, speed and depth of cut were taken as the three control factors at three distinct levels to turn the AA7075 steel. The weighted principal component analysis (WPCA) along with combined-quality-loss (CQL) idea is utilized for the optimization of multiple responses and after that CQL has been enhanced utilizing Taguchi technique. From the Taguchi outcomes, the ideal mix of cutting parameters for greatest material expulsion rate and least surface hardness is acquired at 1500 rpm of speed, 0.2 mm/rev of speed and 0.5 mm of depth of cut. The ANOVA outcomes demonstrate that the feed has superior impact in affecting the multiple responses.