N
N. Muralidharan
Researcher at Kongu Engineering College
Publications - 8
Citations - 83
N. Muralidharan is an academic researcher from Kongu Engineering College. The author has contributed to research in topics: Electrical discharge machining & Microstructure. The author has an hindex of 2, co-authored 7 publications receiving 57 citations. Previous affiliations of N. Muralidharan include Anna University.
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Microstructure and mechanical behavior of AA2024 aluminum matrix composites reinforced with in situ synthesized ZrB2 particles
TL;DR: In this article, the inorganic salts were added to molten aluminum alloy at an elevated temperature of 850OC and the results were studied by applying conventional microcopy and advanced characterization techniques.
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Optimization of CNC-WEDM Parameters for AA2024/ZrB2 in situ Stir Cast Composites Using Response Surface Methodology with Desirability Function Technique
TL;DR: In this article, the machining performance of as-prepared aluminum zirconium diboride AA2024-ZrB2 was investigated for phase identification using X-ray diffraction technique; microstructure analysis using both optical microscope and field emission scanning electron microscope; and analysis of mechanical properties using tensile strength and micro-hardness tests.
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CNC wire-cut EDM input variables analysis on Ni -based superalloy (MONEL K-500)
TL;DR: In this paper, the authors describe a WEDM machining process to produce exact and accurate complex shape products with high corrosion resistance with high hardness and strength, as well as high hardness.
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Structural analysis of mini drone developed using 3D printing technique
TL;DR: 3D printing a quadrotor with a frame of 'X' shaped in structure and the dimension range is less than 100*100 mm which makes it ideal for production on an industrial scale which will aid in many applications like collecting data and surveillance in military operations.
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Material subtraction study of AISI T-15-HSS by wire cut electrical discharge machining (CNC-wire cut EDM) based on Taguchi grey relational analysis
TL;DR: In this article, the problem of wire cut electrical discharge machining is solved by grey relational and statistical analysis like the Taguchi-based design and developed empirical relation will indicate the relationship between machining performance and the process parameters, which will be useful for both machine manufacturers and the machine users.