Abstract
The electrical discharge machining (EDM) is a non-conventional machining process widely used in recent days in the field of aerospace, biomedical, automobile, tool and die industries. Other conventional and non-conventional machining process does the production of EDM electrode, therefore, the cost of production of EDM electrodes account for more than 50% of the cost of the final product. Therefore, additive manufacturing (AM) technology provide the direct fabrication of the EDM electrode. Selective laser sintering (SLS) is the most suitable AM process used for the preparation of EDM tool electrode, that reduce the tool production time and total production cost of the final product. The main difficulty of the production of EDM electrode by the SLS process is the selection of the appropriate material for tool. So that, it can be easily prepared by the SLS process as well as contain the properties of EDM tool electrode. In this work, a newly developed non-conventional metal matrix composite of Al, Si and Mg is prepare directly by SLS process and used as the EDM electrode. To study the EDM performance of the newly prepared AlSiMg electrode, Titanium-alloy (Ti6Al4V) is use as work piece material and commercial grade EDM 30 oil as dielectric fluid. The performance of the newly prepared AlSiMg SLS electrode is compare with conventional copper and graphite electrodes. The EDM is performed by varying different process parameters like open circuit voltage (V), discharge current (Ip), duty cycle (τ) and pulse-on-time (Ton). Three responses like material removal rate (MRR), tool wear rate (TWR) and average surface roughness (Ra) are used to analyze study the EDM process. To reduce the number of experiments, design of experiment (DOE) approach like Taguchi’s L27 orthogonal array is used. The three output responses of the EDM specimens are optimized by GRA method combined with Firefly algorithm and the best parametric setting is reported for the EDM process.
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Sahu, A.K., Mahapatra, S.S. (2019). Optimization of Electrical Discharge Machining of Titanium Alloy (Ti6Al4V) by Grey Relational Analysis Based Firefly Algorithm. In: AlMangour, B. (eds) Additive Manufacturing of Emerging Materials. Springer, Cham. https://doi.org/10.1007/978-3-319-91713-9_2
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