Parametric Optimization of Al₂O₃–ZrO₂ (Y₂O₃) Based Self-Lubricating Composite Cutting Tools for Increasing Shear Angle and Tool Wear Reduction Using Grey-Taguchi Analysis

In the present investigation, self-lubricating cutting tools (SLTs) were fabricated by adding various additives such as NiCr, Ag, Mo, SrSO_4, and CaF₂ to Zirconia Toughened Alumina in order to overcome the difficulties that occurred in dry machining. Three significant process parameters; cutting speed (50 m/min, 125 m/min, 200 m/min, and 275 m/min), feed rate (0.1 mm/rev and 0.2 mm/rev), and depth of cut (0.1 mm and 0.2 mm) were selected for machining process. The experimental runs were conducted with Taguchi L₈ mixed-level orthogonal array. The Grey-Taguchi technique has been employed to convert the multi-decision criteria into a single-decision criterion for performance measures like chip thickness ratio (r), shear angle (Ø), and tool wear. Turning experiments have been performed on the AISI 4340 steel workpiece employing various combinations of machining parameters. The findings revealed that the incorporation of SrSO₄ and Mo at 10 wt% and CaF₂ at 5 wt% (SLT₄) achieved better hardness and wear resistance owing to the development of a self-lubrication layer on rake surface of a tool. A confirmation experiment has been executed in order to verify the outcomes in the end. Finally, there is a noticeable improvement in the outcomes compared to the base cutting tool, i.e., chip thickness ratio is 35.77%, shear angle is 27.31%, and tool wear is 58%. The mechanism for improving performance measures is discussed in detail.