Measurement and optimization of surface roughness and tool wear via grey relational analysis, TOPSIS and RSA techniques. (January 2016)

• Record Type: Journal Article
• Authors: Ramesh, S.; Viswanathan, R.; Ambika, S.
• Is Part Of: Measurement. Volume 78(2016:Jan.)
• Page Start: 63
• Page End: 72
• Publication Date: 2016-01
• Subjects: Magnesium -- Surface roughness -- Flank wear -- TOPSIS -- Optimization; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2015.09.036
• Languages: English
• ISSNs: 0263-2241

Abstract

Graphical abstract: Highlights: Magnesium alloy is considered as "Exotic" and needs attention while machining. The effect of cutting parameters on surface roughness and tool wear have been investigated. This study uses different optimization techniques of GRA and TOPSIS for choosing optimal cutting parameters. The quadratic polynomial model has been generated to predict the surface roughness and tool wear and justified through ANOVA. Abstract: Magnesium alloy (Mg alloy) is one among the lightest materials and which has wide applications in the production of aircraft engines, airframes, helicopter components, light trucks, automotive parts and computers parts for its attractive properties. In this paper, a study to analyze the turning properties of magnesium alloy AZ91D in dry condition with polycrystalline diamond (PCD) cutting inserts is presented. Firstly, to investigate turning of magnesium alloy using grey relational analysis and TOPSIS of optimum cutting parameter values. Secondly, to determine using response surface analysis of mathematical model depending on cutting parameters of surface roughness and tool flank wear in turning. The adequacy of the developed mathematical model is proved by ANOVA. The findings from the investigation showed that feed rate and cutting speed are the dominant factors for surface roughness and tool flank wear respectively.