Multi-response optimization of turning parameters for machining glass fiber–reinforced plastic composite rod

Glass fiber–reinforced plastics are extensively applied in engineering fields as a potential replacement to conventional steels, owing to its corrosive resistance property and high specific strength. But machining is complicated due to its anisotropic properties and non-homogeneous structure. In machining processes, minimum surface roughness and less tool wear are important factors influencing the quality of the surface, tool life, and productivity. Thus, the selection of tool and optimizing machining parameters are essential for perfect finishing. The tool used in this study is TiCN/TiN coated. The cutting parameters applied are cutting speed, feed, and depth of cut. As a dynamic approach, the multiple response optimization is carried out using grey relational analysis and desirability function analysis for simultaneous evaluation. These two methods are considered in optimization, as both are multiple criteria evaluation and not much complicated. Analysis of variance is employed to classify the significant parameters affecting the response.

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