Multi objective optimisation of thermally enhanced machining parameters of Inconel 718 using grey relational analysis

Abstract

Abstract:The present work investigates an experimental study of thermally enhanced machining of nickel-based superalloy Inconel 718 using uncoated tungsten carbide inserts. An inexpensive flame heating technique using an oxyacetylene flame is used as a heat source for thermal enhancement of workpiece. The effects of cutting parameters like cutting speed, feed rate, depth of cut and temperature of workpiece on the performance characteristics like surface roughness, tool wear and material removal rate were studied. A L 27 orthogonal array with four parameters and three levels was adopted for experimental design. Multi response optimisation was done using grey relation analysis to simultaneously minimise surface roughness, tool wear and to maximise material removal rate. It was observed that at cutting speed at 85.21 m/min, feed rate at 0.048 m/min, depth of cut at 0.6 mm and workpiece temperature at 600°C were optimal cutting parameters. It is clearly shown that the above performance characteristics in thermally enhanced machining can be improved effectively through this approach.Keywords: thermally enhanced machining; surface roughness; tool wear; metal removal rate; MRR; Taguchi-based grey relation analysis; ANOVA.Reference to this paper should be made as follows: Ganta, V., Srinivasa Sagar, K. and Chakradhar, D. (2017) 'Multi objective optimisation of thermally enhanced machining parameters of Inconel 718 using grey relational analysis', Int.