BibTeX:

@article{IJIRSTV2I3006,
     title={Optimization of MRR and TWR on EDM by using Taguchi's Method and ANOVA Die Steel H13 },
     author={Suresh Kumar Gurjar and Rajeev Kumar},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={2},
     number={3},
     pages={22--28},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV2I3006.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Electrical Discharge Machining (EDM) is a non-traditional machining process where intricate and complex shapes can be machined. Only electrically conductive materials can be machined by this process and is one of the important machining processes for machining high strength, temperature-resistant (HSTR) alloys. It is capable of machining geometrically complex or hard materials, that are precise and difficult-to-machine such as heat treated tool steels, composites, super alloys, ceramics, carbides, heat resistant steels etc. These materials are being widely used in die and mould making industries, aerospace, aeronautics and nuclear industries. In this work Die steel H13 tool steel is the material used for the machining purpose. For achieving the best performance of the EDM process, it is crucial to carry out parametric design responses such as Material Removal Rate and Tool Wear Rate. It is essential to consider was used to reduce the total number of experiments. Parts of the experiment were conducted with the L9 orthogonal array based on the Taguchi method. Moreover, the signal-to-noise ratios associated with the observed values in the experiments were determined by which factor is most affected by the Responses of Material Removal Rate (MRR) and Tool Wear Rate (TWR). In the present work, Optimization of MRR and TWR on EDM conducted by using Taguchi and ANOVA.

EDM, Optimization Of MRR & Tool Wear Rate, Taguchi’s Method, ANOVA