Si₃N₄–TiN conductive ceramic composites: topography on EDMed surfaces and precise drilled holes

Abstract

In this study, it is challenging to drill a 5 mm hole in a Si3N4–TiN conductive ceramic composite, specifically when attempting to identify an association between EDM machining inputs such as current, pulse on-time, pulse off-time, dielectric pressure and spark gap and performance parameters like as Material Removal Rate, Electrode Wear Rate, Average Surface Roughness, and geometrical tolerances such as Cylindricity, Circularity and perpendicularity. The study examines the surface deformations of a composite comprising EDAX report, machined electrode and molybdenum wire following WEDM machining. Current of 5A, Pulse on-time of 9µs, Pulse off-time of 7µs, spark gap of 0.15 mm, dielectric pressure of 21.0 kg/cm2, material removal rate of 0.004214 g/min, electrode wear rate of 0.000245 g/min and surface roughness of 0.349 µm were found to be optimal. The experimental findings show that good surface finish may be attained on a copper electrode-machined surface, along with improved machining accuracy, closer geometrical tolerances and lesser anomalies.

Optimizing the Electrical Discharge Machining Process Parameters of the Nimonic C263 Superalloy: A Sustainable Approach

“…The study reported the form (perpendicularity) tolerance index for Inconel 718 to be in the range of 50-55 (dimensionless, scaled by the machining time) and for Inconel 625, in the range of 15-20 (dimensionless, scaled by the machining time) for higher values of the peak current. Selvarajan et al [8] explored the effect of EDM drilling process parameters like the current, pulse on-time, pulse off-time, dielectric pressure, and spark gaps on performance parameters such as the material removal rate, electrode wear rate, and average surface roughness, and on geometrical tolerances such as the cylindricity, circularity and perpendicularity of drilled holes in Si3N4-TiN composites. The experimental results indicate that utilizing a copper electrode for machining can yield a favorable surface finish, accompanied by enhanced machining accuracy, tighter geometrical tolerances, and reduced irregularities.…”

Simulation and Optimization of Surface Roughness and Process Performance during Machining of HSS by Micro-WEDM Technology

“…These reasons led us to perform experimental research, the goal of which was to achieve significant progress in optimizing the quality of the machined surface while maintaining high productivity of the electrical discharge process. At the same time, we would like to contribute to the database of already existing knowledge through clear formulations of particular laws in relation to the processes that take place directly on the machined surface during the electrical discharge [ 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 ].…”

Prediction and Multiparametric Optimization of the Machined Surface Quality of Tool Steels in Precise Wire Electrical Discharge Machining

“…They demonstrated that the proposed neural network model enhanced with optimized machining parameters is effective in estimating the MRR. The extensive experimental research carried out, as described in the works of several authors [30][31][32][33][34], demonstrates that there is a wide range of input parameters for the electrical discharge process, which significantly affect the output qualitative parameters of machined surfaces in addition to the quantitative performance parameters of the process. Therefore, researchers [35][36][37][38][39][40][41][42], who solved the problem of multi-objective optimization of various Non-Traditional Machining processes (NTM) using an a priori approach, provided a different perspective on the issue.…”