Multi objective optimisation of thermally enhanced machining parameters of Inconel 718 using grey relational analysis
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Date
2017
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Publisher
Inderscience Publishers
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 L27 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. © © 2017 Inderscience Enterprises Ltd.
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Keywords
Analysis of variance (ANOVA), Carbide cutting tools, Cutting, Multiobjective optimization, Nickel alloys, Surface roughness, Tungsten carbide, Turning, Wear of materials, Grey relation analysis, Grey relational analysis, Metal removal rate, Nickel- based superalloys, Optimal cutting parameters, Performance characteristics, Tool wear, Workpiece temperature, Cutting tools
Citation
International Journal of Machining and Machinability of Materials, 2017, 19, 1, pp. 57-75
