Determination of optimum parameters for multi-performance characteristics in turning by using grey relational analysis

Optimization of multi-criteria problems is a great need of producers to produce precision parts with low costs. Optimization of multi-performance characteristics is more complex compared to optimization of single-performance characteristics. The theory of grey system is a new technique for performing prediction, relational analysis, and decision making in many areas. In this paper, the use of grey relational analysis for optimizing the turning process parameters for the workpiece surface roughness and the chip thickness is introduced. Various turning parameters, such as cutting speed, feed rate, tool nose radius, and concentration of solid–liquid lubricants (minimum-quantity lubricant) were considered. A factorial design with eight added center points was used for the experimental design. Optimal machining parameters were determined by the grey relational grade obtained from the grey relational analysis for multi-performance characteristics (the surface roughness and the chip thickness). The results of confirmation experiments reveal that grey relational analysis coupled with factorial design can effectively be used to obtain the optimal combination of turning parameters. Experimental results have shown that the surface roughness and the chip thickness in the turning process can be improved effectively through the new approach. The minimum surface roughness and smallest chip thickness are 9.83 and 0.32 mm, respectively, obtained at optimal conditions of cutting speed, 1,200 rpm; feed rate, 0.06 mm/rev; nose radius, 0.8 mm; and concentration of solid–liquid lubricant (10% boric acid + SAE-40 base oil).

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