Optimization Of Process Parameters Affecting Cutting Force, Power Consumption And Surface Roughness Using Taguchi-Based Gray Relational Analysis In Turning Aisi 1040 Steel

This study focuses on optimization of cutting conditions and modeling of cutting force (Fc), power consumption (P), and surface roughness (Ra) in machining AISI 1040 steel using cutting tools with 0.4mm and 0.8mm nose radius. The turning experiments have been performed in CNC turning machining at three different cutting speeds Vc (150, 210 and 270m/min), three different feed rates f (0.12 0.18 and 0.24mm/rev), and constant depth of cut (1mm) according to Taguchi L18 orthogonal array. Kistler 9257A type dynamometer and equipment’s have been used in measuring the main cutting force (Fc) in turning experiments. Taguchi-based gray relational analysis (GRA) was also applied to simultaneously optimize the output parameters (Fc, P and Ra). Moreover, analysis of variance (ANOVA) has been performed to determine the effect levels of the turning parameters on Fc, P and Ra. Then, the mathematical models for the output parameters (Fc, P and Ra) have been developed using linear and quadratic regression models. The analysis results indicate that the feed rate is the most important factor affecting Fc and Ra, whereas the cutting speed is the most important factor affecting P. Moreover, the validation tests indicate that the system optimization for the output parameters (Fc, P and Ra) is successfully completed with the Taguchi method at a significance level of 95%.