Ranjeet Kumar Sahu
Papers
1
Total Citations
6
H-Index
1
About
Ranjeet Kumar Sahu is a materials and manufacturing researcher whose work focuses on optimizing advanced machining processes for difficult-to-cut alloys. His primary research areas include wire electrical discharge machining (WEDM), non-traditional manufacturing techniques, and multi-objective optimization using metaheuristic algorithms. Sahu’s most cited work, published in 2023, demonstrates a novel approach to machining parameter optimization for Ni50.3Ti29.7Hf20—a shape memory alloy with high strength and thermal stability. By integrating the TOPSIS decision-making method with the Grey Wolf Optimization algorithm, he achieved significant improvements in material removal rate and surface quality, offering a robust framework for industrial applications. This paper has garnered 6 citations, reflecting its relevance to researchers seeking efficient machining solutions for advanced alloys. Sahu’s contributions are particularly notable for bridging computational optimization and practical manufacturing challenges, providing a replicable methodology for process parameter selection. His work is valuable for students and engineers working in aerospace, biomedical, and automotive sectors where precision machining of superalloys is critical.
Research Focus
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Top Papers
- 1