Mr SATISH CHAURASIA, NIT Meghalaya, India
Mr. Satish Chaurasia is a Ph.D. candidate in Advanced Manufacturing Technologies at the National Institute of Technology, Meghalaya. His research focuses on Micro-EDM machining of Nitinol Shape Memory Alloys (SMA) using bio-based dielectrics, aiming to optimize machining processes for medical applications. His work integrates Artificial Neural Networks (ANN) and Genetic Algorithms (GA) for predictive modeling, ensuring efficiency and reproducibility. Mr. Chaurasia has published in prestigious journals and is known for his contributions to biocompatibility testing, including cytotoxicity and hemocompatibility studies. His innovative research in sustainable, bio-grade materials and manufacturing processes positions him as a leader in the field. 🛠️💡💉🌱
Publication Profile
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Academic and Professional Background🎓
Mr. Satish Chaurasia is currently pursuing a Ph.D. in Advanced Manufacturing Technologies at the National Institute of Technology, Meghalaya, with a focus on Micro-EDM machining of Nitinol Shape Memory Alloys (SMA) using bio-based dielectrics. His research aims to optimize machining processes for medical applications, using sustainable materials to reduce environmental impact. He holds an M.Tech in Mechanical Engineering from Madan Mohan Malaviya University of Technology, Gorakhpur, U.P., India. His academic background, combined with his innovative research in non-traditional machining, positions him as a promising leader in advanced manufacturing and medical device development. 🎓🔧💡🌱
Research Focus Area 🌱🧬
Mr. Satish Chaurasia’s research interests are focused on the micro-EDM machining of bio-grade materials, particularly Nitinol Shape Memory Alloys (SMA), which are essential for medical devices. He explores the use of bio-based dielectrics, such as sesame and canola oils, to optimize machining processes while minimizing environmental impact. His work involves process parameter optimization, including factors like tool rotation, voltage, and pulse duration. Additionally, he conducts surface morphology and biocompatibility analyses to ensure performance and safety. Mr. Chaurasia also leverages Artificial Neural Networks (ANN) and Genetic Algorithms (GA) for predictive modeling to enhance machining efficiency. ⚙️🌱🔬🤖
Publication Top Notes📄✨
Self-similar solution for the flow behind an exponential shock wave in a rotational axisymmetric non-ideal gas with magnetic field
On the blast wave propagation and structure in a rotational axisymmetric perfect gas
Exact solution for isothermal flow behind a shock wave in a self-gravitating gas of variable density in an azimuthal magnetic field
Optimization of Kerf Width in WEDM of Sandwich Woven CFRP-An Ensemble Machine Learning Based Approach
A novel investigation on rotary tool-assisted electrical discharge-micro drilling of carbon-aramid hybrid composite
Modelling, Measurement and Control B
Powder mixed micro-electric discharge milling of Ni-rich NiTi SMA: an investigation on machining performance and biocompatibility
Electrical discharge machining of super alloy incoloy 925: a study based on box behnken design and response surface methodology
Hybrid Electro Discharge Machining Process Investigation: A review
Conclusion
Mr. Satish Chaurasia’s cutting-edge research in non-traditional machining, his focus on sustainable, bio-based materials for medical applications, and his use of advanced machine learning techniques for process optimization makes him an excellent candidate for the Best Researcher Award. His research not only pushes the boundaries of manufacturing technology but also addresses the pressing need for environmentally friendly, biocompatible solutions in the medical field.