LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Multi-objective optimization using Taguchi based grey relational analysis in turning of Rock dust reinforced Aluminum MMC

Photo from wikipedia

Abstract The present work deals with the optimization of material and machining parameters for surface finish and Material Removal Rate (MRR) enhancements while turning Aluminium/Rock dust composite through Taguchi and… Click to show full abstract

Abstract The present work deals with the optimization of material and machining parameters for surface finish and Material Removal Rate (MRR) enhancements while turning Aluminium/Rock dust composite through Taguchi and Grey Relational Analysis (GRA). Rock dust particles weight percent (5, 10 & 15%) and particle size (10, 20 & 30 μm) are varied accordingly to investigate the effect of reinforcement parameters on composite properties. Along with reinforcement weight % and particle size, also the turning parameters viz. speed, feed and depth of cut are chosen as input parameters with surface roughness (Ra) and MRR as responses. CNC turning is performed based on the L27 orthogonal array designed by Taguchi approach. Results expose that feed has remarkable effect on Ra and MRR rather than any of the other parameters examined. The optimum parameter combination identified through Multi criteria optimization technique GRA is S2W2N3F1D3 and the improvement in GRG approximates to 0.194.

Keywords: grey relational; relational analysis; rock dust; rock

Journal Title: Measurement
Year Published: 2020

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.