Open Access

Enhancing Surface Quality and Tool Longevity in EDM of D2 Steel Using Copper Composite Tools

Navuluri Padma Sravya, Department of Mechanical Engineering, Geethanjali Institute of Science & Technology, Nellore, AP, India R. Manimegalai, Department of Physics, K. Ramakrishna College of Engineering, Samayapuram, Trichy, TN, India R. Rajeswari, Department of Biotechnology, P.S.R Engineering College, Sivakasi, TN, India M. Gowtham, Department of Electrical and Electronics Engineering, Karpagam Institute of Technology, Coimbatore, TN, India R. S. Achsah, Department of Biotechnology, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Vellanur, Avadi, Chennai, TN, India S. Naveen naveenmurali33@gmail.com
Department of Mechanical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, TN, India

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Abstract

Hard material machining and die manufacture are the main applications for electrical discharge machining (EDM). For EDM, conventional electrode materials include graphite, steel, brass, pure copper, and alloys based on copper. Unfortunately, excessive tool wear is a common problem with these materials, which raises the cost of machining. In this investigation, hardened D2 steel was machined using a composite tool made of 90% copper and 10% silicon carbide. The powder metallurgy method was used to create the composite tool. Surface roughness (SR) and electrode wear rate (EWR) were compared to a number of process variables. For experimentation, a response surface methodology based on CCD design in design of experts software was used. SR and electrode wear rate models were created using the CCD approach. Utilizing analysis of variance, the most important factors and their effects on EWR and SR were determined. The lowest tool wear rate of 0.39 gm/min is achieved with a current of 5 Amps, a pulse duration of 100 µs, and a pulse interval of 10 µs with an R2 of 0.9957, which accounts for 99.57% of the variability, the tool wear rate model fits the data very well and obtained lowest surface roughness of 2.8 µm.

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