Application of Grey relational analysis in high speed machining of AA (6351)-SiC-B4C hybrid composite. (2015)

• Record Type: Journal Article
• Authors: Kumaran, S. Thirumalai; Uthayakumar, M.; Slota, Adam; Zajac, Jerzy
• Is Part Of: International journal of material & product technology. Volume 51:Number 1(2015)
• Page Start: 17
• Page End: 31
• Publication Date: 2015
• Subjects: surface roughness -- power consumption -- material removal rate -- MRR -- grey relational analysis -- GRA -- analysis of variance -- ANOVA -- high speed machining -- hybrid composites -- aluminium alloys -- silicon carbide -- boron carbide -- polycrystalline diamond -- PCD tools -- composites machining -- cutting speed -- feed -- depth of cut -- analysis of variance -- ANOVA -- signal to noise ratio -- SNR; Manufacturing processes -- Periodicals; Materials -- Testing -- Periodicals; 620.11
• Languages: English
• ISSNs: 0268-1900

Abstract

This paper presents an effective approach for the optimisation of cutting conditions in machining aluminium alloy (6351) matrix reinforced with 5 wt. % silicon carbide (SiC) and 5 wt. % of boron carbide (B4 C) with multiple performance characteristics based on the grey relational analysis. Machining study was carried out with polycrystalline diamond (PCD) tool to identify optimum cutting parameters with an objective to minimise the surface roughness, power consumption and to maximise the material removal rate. The main factors deciding the above objectives are cutting speed, feed and depth of cut. Analysis of variance (ANOVA) is performed and signal-to-noise (S/N) ratio is determined to understand the significant level of each cutting parameters. The experimental results showed that the cutting speed exerted the greatest effect on the machining of the composite (51.37%) followed by the feed (36.65%) and depth of cut (11.66%). The optimised cutting parameters are then verified through a confirmation experiment.